From 7411f0ad5117eff433a150b71442c1d92f69bb68 Mon Sep 17 00:00:00 2001
From: Chris Davies <cdavies@cosmogw.kosmo.physik.uni-muenchen.de>
Date: Fri, 7 Oct 2022 13:56:47 +0200
Subject: [PATCH 01/14] added a new module "modelling.py" to allow for forward
 modelling and testing systematics. Includes functionality to create 2D nfw
 shear and convergence maps, kaiser-squires transformation and angular and
 radial profiles.

---
 clmm/modelling.py | 245 ++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 245 insertions(+)
 create mode 100644 clmm/modelling.py

diff --git a/clmm/modelling.py b/clmm/modelling.py
new file mode 100644
index 000000000..a257f6c47
--- /dev/null
+++ b/clmm/modelling.py
@@ -0,0 +1,245 @@
+from astropy.cosmology import LambdaCDM
+from astropy import constants as const
+from astropy import units as u
+import numpy as np
+import matplotlib.pyplot as plt
+
+class profiles:
+    
+    def __init__(self,M,c,z_l,z_s,sig=False):
+        import numpy as np
+        from astropy.cosmology import FlatLambdaCDM
+        from astropy import constants as const
+        from astropy import units as u
+        
+        self.M = M
+        self.c = c
+        self.z_l = z_l
+        self.z_s = z_s
+        self.sig = sig
+        
+        self.cosmology()
+        
+        return
+    
+    def cosmology(self, H_0 = 70., Omega_m = 0.3, Omega_Lambda = 0.7, Tcmb0=2.725):
+        
+        self.H_0 = H_0
+        self.Omega_m = Omega_m
+        self.Tcmb0 = Tcmb0
+        self.Omega_Lambda = Omega_Lambda
+        
+        return
+        
+        
+    def get_r_vals(self,nbins,lower_r,upper_r,log=False):
+        '''create radial bins for profiles
+        nbins: number of bins
+        lower_r: lowest bin value
+        upper_r: highest bin value
+        returns bin edges in units provided, or kpc if none are provided
+        '''
+        #create r values
+        self.nbins = nbins
+        self.lower_r = lower_r
+        self.upper_r = upper_r
+        self.log_r_vals = log
+        
+        
+        if self.log_r_vals:
+            if self.lower_r == 0:
+                raise ValueError('log(lower_r) cannot be evaluated for lower_r = 0')
+                
+            r_vals = np.logspace(np.log10(self.lower_r),np.log10(self.upper_r),self.nbins+1)
+            
+        if not self.log_r_vals:
+            r_vals = np.linspace(self.lower_r,self.upper_r,self.nbins+1)
+        
+        #if no units are provided, set units to kpc, otherwise keep input units
+        r_vals *= u.dimensionless_unscaled
+        if r_vals.unit == u.dimensionless_unscaled:
+            r_vals *= u.kpc
+            
+        self.r_vals = r_vals
+        return self.r_vals
+    
+    def kappa_NFW(self,r_vals=None):
+        '''r_vals: radial bin values for halo lensing profile
+           M: halo mass
+           c: concentration
+           z_l: lens redshift
+           z_s: source redshift
+           delta_sig: If False, return convergence profile, if True, return delta Sigma profile
+        '''
+        
+        if np.all(r_vals.value) == None:
+            r_vals = self.r_vals
+        
+        cosmo = LambdaCDM(H0=self.H_0, Om0=self.Omega_m, Ode0=self.Omega_Lambda, Tcmb0=self.Tcmb0)
+
+        r_200 = ( (const.G * self.M)/(100. * cosmo.H(self.z_l)**2) )**(1./3.)
+        r_s = r_200 * self.c
+        delta_c = (200./3.) * ( self.c**3 / ( np.log(1+self.c) - ( self.c/(1+self.c) ) ) )
+        
+        x = r_vals/r_s
+
+        Sigma_crit_coeff = const.c**2 / (4. * np.pi * const.G)
+
+        D_s = cosmo.angular_diameter_distance(self.z_s)  
+        D_d = cosmo.angular_diameter_distance(self.z_l)  
+        D_ds = cosmo.angular_diameter_distance_z1z2(self.z_l,self.z_s)  
+
+        Sigma_crit = Sigma_crit_coeff * D_s / (D_d * D_ds)
+
+        k_s = cosmo.critical_density(self.z_l) * delta_c * r_s
+
+        coeff = 2.*k_s / (x**2 - 1.)
+
+        f_internal = 1. - (2./np.lib.scimath.sqrt(1.-x**2)) * np.arctanh(np.lib.scimath.sqrt((1.-x)/(1.+x)))
+
+        nfw = coeff * f_internal
+
+        if self.sig:
+            return nfw.to(const.M_sun / u.Mpc**2).real
+        if not self.sig:
+            return (nfw.real / Sigma_crit).decompose()
+
+    def make_grid(self,npix,r_max):
+        '''make 2D grid centered on origin
+        npix: resolution of grid
+        r_max: width of grid is 2*r_max
+        '''
+        
+        npix *= 1j #imaginary so that ogrid knows to interpret npix as array size
+        y,x = np.ogrid[-r_max:r_max:npix,-r_max:r_max:npix]
+        r_2D = np.hypot(y,x)
+        
+        return r_2D
+
+    def kappa_NFW_2D(self,npix,r_max):
+        
+        '''create 2D NFW profile on grid
+        '''
+        
+        self.npix = npix
+        self.r_max = r_max
+        r_2D = self.make_grid(self.npix,self.r_max)
+        
+        return self.kappa_NFW(r_2D)
+
+
+
+def KaiserSquires(Sigma):
+
+    kappa_tilde = np.fft.fft2(Sigma)
+
+    k = np.fft.fftfreq(kappa_tilde.shape[0])
+
+    oper_1  = - 1./(k[:, None]**2 + k[None, :]**2) * (k[:, None]**2 - k[None, :]**2)
+    oper_2  = - 2./(k[:, None]**2 + k[None, :]**2) * k[:, None]*k[None, :]
+
+    oper_1[0, 0] = -1
+    oper_2[0, 0] = -1
+
+    e1_tilde = oper_1*kappa_tilde
+    e2_tilde = oper_2*kappa_tilde
+
+    e1 = np.fft.ifft2(e1_tilde).real
+    e2 = np.fft.ifft2(e2_tilde).real
+
+    return e1, e2
+
+def getTangetial(e1, e2, center, dx=10./1000.):
+
+    n = e1.shape[0]
+
+    xx = np.arange(-n/2, n/2)*dx
+
+    XX, YY = np.meshgrid(xx, xx)
+
+    center_1, center_2 = center
+
+    from_cent_1 = XX - center_1
+    from_cent_2 = YY - center_2
+
+    angle = -np.sign(from_cent_2)*np.arccos(from_cent_1/np.sqrt(from_cent_1**2+from_cent_2**2))
+    radius = np.sqrt(from_cent_1**2+from_cent_2**2)
+
+    angle[np.isnan(angle)] = 0
+
+    et = - e1*np.cos(2*angle) - e2*np.sin(2*angle)
+    ex = + e1*np.sin(2*angle) - e2*np.cos(2*angle)
+
+    return et, ex, radius, angle
+
+def getRadial(radius_map,r_bins,angle_map,phi_bins,kappa_map,et_map):
+
+    _N = np.zeros((len(r_bins)-1, len(phi_bins)-1))
+    _K = np.zeros((len(r_bins)-1, len(phi_bins)-1))
+    _GT = np.zeros((len(r_bins)-1, len(phi_bins)-1))
+
+    ii_r = np.digitize(radius_map, r_bins) - 1
+    ii_phi = np.digitize(angle_map, phi_bins) - 1
+    
+    for i_r, i_phi, kk, gg in zip(ii_r.flatten(), ii_phi.flatten(), kappa_map.flatten(), et_map.flatten()):
+
+        _N[i_r, i_phi] += 1
+        _K[i_r, i_phi] += kk
+        _GT[i_r, i_phi] += gg
+
+    kappa_radial = _K/_N
+    gammat_radial = _GT/_N
+    
+    return kappa_radial,gammat_radial
+
+
+def plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map,ex_map,
+                       kappa_radial,gammat_radial,r_bins):
+    
+    fig, ax = plt.subplots(2,3,figsize=[9,6])
+    ax.ravel()
+    
+    ax[0,0].imshow(kappa_map,origin = 'lower')
+    ax[0,0].set_title(r'$\kappa$')
+
+
+    ax[0,1].imshow(e1_map,origin = 'lower')
+    ax[0,1].set_title(r'$e_1$')
+
+
+    ax[0,2].imshow(e2_map,origin = 'lower')
+    ax[0,2].set_title(r'$e_2$')
+
+
+    ax[1,0].imshow(et_map,origin = 'lower')
+    ax[1,0].set_title(r'$e_t$')
+
+
+    ax[1,1].imshow(ex_map,origin = 'lower')
+    ax[1,1].set_title(r'$e_x$')
+
+    
+    
+    r_bins_mid = 0.5 * (r_bins[1:] + r_bins[:-1])
+
+    ax[1,2].plot(r_bins_mid, kappa_radial.mean(axis=-1), label=r'$\kappa(r)$')
+    ax[1,2].plot(r_bins_mid, gammat_radial.mean(axis=-1), label=r'$\gamma_t(r)$')
+    
+    plt.legend()
+    plt.show()
+    
+    fig,ax = plt.subplots(1,2)
+    
+    ax[0].imshow(kappa_radial,origin='lower')
+    ax[1].imshow(gammat_radial,origin='lower')
+    
+    ax[0].set_ylabel('r')
+    ax[0].set_xlabel('$\phi$')
+    
+    ax[1].set_ylabel('r')
+    ax[1].set_xlabel('$\phi$')
+    
+    ax[0].set_title(r'$\kappa$')
+    ax[1].set_title(r'$\gamma_t$')
+
+    plt.show()

From 9471d8eec10d78d006ef0dbe827230069a6e9063 Mon Sep 17 00:00:00 2001
From: Chris Davies <cdavies@cosmogw.kosmo.physik.uni-muenchen.de>
Date: Fri, 7 Oct 2022 13:59:48 +0200
Subject: [PATCH 02/14] added a demo notebook to demonstrate functionality of
 modelling.py

---
 examples/demo_modelling.ipynb | 12663 ++++++++++++++++++++++++++++++++
 1 file changed, 12663 insertions(+)
 create mode 100644 examples/demo_modelling.ipynb

diff --git a/examples/demo_modelling.ipynb b/examples/demo_modelling.ipynb
new file mode 100644
index 000000000..06cd1aece
--- /dev/null
+++ b/examples/demo_modelling.ipynb
@@ -0,0 +1,12663 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "45308159",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "%config InlineBackend.figure_format = 'svg'\n",
+    "\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import sys\n",
+    "sys.path.append('/home/cdavies/CLMM/')\n",
+    "import clmm\n",
+    "from clmm import Cosmology\n",
+    "from clmm.support import mock_data as mock\n",
+    "from clmm.galaxycluster import GalaxyCluster\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "import clmm.utils as u\n",
+    "\n",
+    "from modelling import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7ba07a0d",
+   "metadata": {},
+   "source": [
+    "Make sure we know which version we're using"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "bbd94d3a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'1.0.1'"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "clmm.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "66c330d7",
+   "metadata": {},
+   "source": [
+    "The modelling module can be used to create 2D lensing maps. This allows us to forward model systematics, starting at the map level. In this notebook, we use miscentering as an example systematic."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "8aea13a2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Define the center of the map (in Mpc)\n",
+    "center_1 = 0\n",
+    "center_2 = 0\n",
+    "\n",
+    "#define radial and angular bins\n",
+    "N_r_bins = 30\n",
+    "N_phi_bins = 25\n",
+    "r_bins = np.insert(np.logspace(-2, 1, N_r_bins), 0, 0)\n",
+    "phi_bins = np.linspace(-np.pi, np.pi+0.01, num=N_phi_bins+1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "909edd57",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#specify parameters for NFW halo\n",
+    "c = 1 #concentration\n",
+    "z_l = 1.0 #lens redshift\n",
+    "z_s = 2.0 #source redshift\n",
+    "Mass = 1E13 * const.M_sun\n",
+    "\n",
+    "#define physical size of grid\n",
+    "units = u.mpc\n",
+    "r_max = 10 * units\n",
+    "\n",
+    "#number of pixels in grid\n",
+    "npix = 512\n",
+    "\n",
+    "#define physcial size of a pixel\n",
+    "dx = r_max/npix"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "de3d76d6",
+   "metadata": {},
+   "source": [
+    "Now we can create the convergence maps"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "5b51bbc8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: function 'sqrt' is not known to astropy's Quantity. Will run it anyway, hoping it will treat ndarray subclasses correctly. Please raise an issue at https://github.com/astropy/astropy/issues.  [astropy.units.quantity]\n"
+     ]
+    }
+   ],
+   "source": [
+    "#lensing_map has the option to return either Sigma map or the convergence map.\n",
+    "lensing_map = profiles(Mass, c, z_l, z_s, sig=False) \n",
+    "#make map\n",
+    "kappa_map = lensing_map.kappa_NFW_2D(npix,r_max)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "b0dc4b6c",
+   "metadata": {},
+   "outputs": [
+    {
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+   "source": [
+    "axlim = 2*r_max.value\n",
+    "plt.imshow(kappa_map,extent=[-axlim,axlim,-axlim,axlim],origin='lower')\n",
+    "plt.xlabel('x ({0})'.format(r_max.unit))\n",
+    "plt.ylabel('y ({0})'.format(r_max.unit))\n",
+    "plt.colorbar().set_label('$\\\\kappa$',rotation=0)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e073090a",
+   "metadata": {},
+   "source": [
+    "Repeat the procedure for a Sigma map"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "2aaf9cb0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#lensing_map has the option to return either Sigma map or the convergence map.\n",
+    "lensing_map = profiles(Mass, c, z_l, z_s, sig=True) \n",
+    "#make map\n",
+    "Sigma_map = lensing_map.kappa_NFW_2D(npix,r_max)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "72993065",
+   "metadata": {},
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+    "axlim = 2*r_max.value\n",
+    "plt.imshow(kappa_map,extent=[-axlim,axlim,-axlim,axlim],origin='lower')\n",
+    "plt.xlabel('x ({0})'.format(r_max.unit))\n",
+    "plt.ylabel('y ({0})'.format(r_max.unit))\n",
+    "plt.colorbar().set_label('$\\\\Sigma [M_\\odot\\; Mpc^{-2}]$',rotation=90)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4b28b017",
+   "metadata": {},
+   "source": [
+    "We can transform from the convergence to the shear with the Kaiser Squires algorithm, returning the e1 and e2 shear maps."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "eec34ea3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/cdavies/CLMM_testing/modelling.py:138: RuntimeWarning: divide by zero encountered in true_divide\n",
+      "  oper_1  = - 1./(k[:, None]**2 + k[None, :]**2) * (k[:, None]**2 - k[None, :]**2)\n",
+      "/home/cdavies/CLMM_testing/modelling.py:138: RuntimeWarning: invalid value encountered in multiply\n",
+      "  oper_1  = - 1./(k[:, None]**2 + k[None, :]**2) * (k[:, None]**2 - k[None, :]**2)\n",
+      "/home/cdavies/CLMM_testing/modelling.py:139: RuntimeWarning: divide by zero encountered in true_divide\n",
+      "  oper_2  = - 2./(k[:, None]**2 + k[None, :]**2) * k[:, None]*k[None, :]\n",
+      "/home/cdavies/CLMM_testing/modelling.py:139: RuntimeWarning: invalid value encountered in multiply\n",
+      "  oper_2  = - 2./(k[:, None]**2 + k[None, :]**2) * k[:, None]*k[None, :]\n"
+     ]
+    }
+   ],
+   "source": [
+    "e1_map, e2_map = KaiserSquires(kappa_map)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "25f42de1",
+   "metadata": {},
+   "source": [
+    "Plot the e1 and e2 maps"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "2ba6da86",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.imshow(e1_map)\n",
+    "plt.colorbar()\n",
+    "plt.show()\n",
+    "\n",
+    "plt.imshow(e2_map)\n",
+    "plt.colorbar()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "12c04b61",
+   "metadata": {},
+   "source": [
+    "from the convergence map we can compute the convergence profile, and from the e1 and e2 maps we can compute the tangential shear profile."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f6af6b7e",
+   "metadata": {},
+   "source": [
+    "The getTangential function uses the e1 and e2 maps as an input, along with a map center, and returns e_tangential and e_cross maps about a given center. \n",
+    "\n",
+    "The function also returns a radius map and an angle map, which is used when computing radial profile with getRadial"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "6b8c1825",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/cdavies/CLMM_testing/modelling.py:165: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  angle = -np.sign(from_cent_2)*np.arccos(from_cent_1/np.sqrt(from_cent_1**2+from_cent_2**2))\n"
+     ]
+    }
+   ],
+   "source": [
+    "et_map, ex_map, radius_map, angle_map = getTangetial(e1_map, e2_map, [center_1, center_2], dx=dx.value)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "e743f1b8",
+   "metadata": {},
+   "outputs": [
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+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.imshow(et_map)\n",
+    "plt.colorbar()\n",
+    "plt.show()\n",
+    "\n",
+    "plt.imshow(ex_map)\n",
+    "plt.colorbar()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cde1c95f",
+   "metadata": {},
+   "source": [
+    "With the radius_map and angle_map, we can calculate the radial convergence profile from the kappa map and the radial tangential shear profile from the e_tangential map, using the getRadial function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "e3d066a0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/cdavies/CLMM_testing/modelling.py:190: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/home/cdavies/CLMM_testing/modelling.py:191: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  gammat_radial = _GT/_N\n"
+     ]
+    }
+   ],
+   "source": [
+    "kappa_radial, gammat_radial = getRadial(radius_map,r_bins,\n",
+    "                                        angle_map,phi_bins,kappa_map,et_map)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f89da817",
+   "metadata": {},
+   "source": [
+    "plot the radial convergence and tangential shear profiles. Note that these profiles are not averaged over all angles yet, meaning that these profiles are 2D (radial and angular). This is useful for miscentering which leaves anisotropic signatures on the resulting lensing profiles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "080ff2f4",
+   "metadata": {},
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+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.imshow(kappa_radial)\n",
+    "plt.show()\n",
+    "\n",
+    "plt.imshow(gammat_radial)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1086e4de",
+   "metadata": {},
+   "source": [
+    "We can recover the 1D radial convergence and tangential shear profiles as follows"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "5c6174be",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "kappa_1D_radial = kappa_radial.mean(axis=-1)\n",
+    "gammat_1D_radial = gammat_radial.mean(axis=-1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ebb41586",
+   "metadata": {},
+   "source": [
+    "Plot the 1D radial profiles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "29a26710",
+   "metadata": {},
+   "outputs": [
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+   ],
+   "source": [
+    "r_bins_mid = 0.5 * (r_bins[1:] + r_bins[:-1])\n",
+    "plt.plot(r_bins_mid,kappa_1D_radial,label='$\\\\kappa(r)$')\n",
+    "plt.plot(r_bins_mid,gammat_1D_radial,label='$\\gamma_t(r)$')\n",
+    "plt.legend()\n",
+    "plt.xlabel('r [Mpc]')\n",
+    "plt.ylabel('Lensing amplitude')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "81e0ceb4",
+   "metadata": {},
+   "source": [
+    "We now repeat the above procedure, but this time we use an incorrect center (relative to the true hale center) when performing the calculations, the exemplify the impact of miscentering"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "13660944",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/cdavies/CLMM_testing/modelling.py:190: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/home/cdavies/CLMM_testing/modelling.py:191: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  gammat_radial = _GT/_N\n"
+     ]
+    }
+   ],
+   "source": [
+    "#First we a define miscentring parameter\n",
+    "R_mis = 1 #Mpc\n",
+    "\n",
+    "#find new center based on R_mis:\n",
+    "_phi_Rmis = 2*np.pi*np.random.random()  # isotropic angle for mis-centering\n",
+    "\n",
+    "# mis-centered coordinates\n",
+    "center_1 = R_mis*np.cos(_phi_Rmis)\n",
+    "center_2 = R_mis*np.sin(_phi_Rmis)\n",
+    "\n",
+    "et_map, ex_map, radius_map, angle_map = getTangetial(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
+    "\n",
+    "kappa_radial, gammat_radial = getRadial(radius_map,r_bins,\n",
+    "                                              angle_map,phi_bins,kappa_map,et_map)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e9720a7d",
+   "metadata": {},
+   "source": [
+    "we can plot all of the results at once using the plot_maps_and_profiles function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "32772d61",
+   "metadata": {},
+   "outputs": [
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+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map,ex_map,\n",
+    "                       kappa_radial,gammat_radial,r_bins)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "510b4c9c",
+   "metadata": {},
+   "source": [
+    "We can also investigate how the 1D radial lensing profiles change as a function of miscentering"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "53fa70dd",
+   "metadata": {},
+   "source": [
+    "Now define a miscentering distribution"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "38b199f1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#define miscentring distribution\n",
+    "R_mis_max = 1 \n",
+    "N_R_mis = 15\n",
+    "R_mis_arr = np.insert(np.logspace(-2, np.log10(R_mis_max), N_R_mis-1), 0, 0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "c17883c2",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/cdavies/CLMM_testing/modelling.py:165: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  angle = -np.sign(from_cent_2)*np.arccos(from_cent_1/np.sqrt(from_cent_1**2+from_cent_2**2))\n",
+      "/home/cdavies/CLMM_testing/modelling.py:190: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/home/cdavies/CLMM_testing/modelling.py:191: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  gammat_radial = _GT/_N\n"
+     ]
+    }
+   ],
+   "source": [
+    "et_map = np.zeros((N_R_mis,kappa_map.shape[0],kappa_map.shape[1]))\n",
+    "ex_map = np.zeros(et_map.shape)\n",
+    "radius_map = np.zeros(et_map.shape)\n",
+    "angle_map = np.zeros(et_map.shape)\n",
+    "\n",
+    "kappa_radial = np.zeros((N_R_mis,N_r_bins,N_phi_bins))\n",
+    "gammat_radial = np.zeros(kappa_radial.shape)\n",
+    "\n",
+    "for j in range(len(R_mis_arr)):\n",
+    "\n",
+    "    _phi_Rmis = 2*np.pi*np.random.random()  # isotropic angle for mis-centering\n",
+    "\n",
+    "    # mis-centered coordinates\n",
+    "    center_1 = R_mis_arr[j]*np.cos(_phi_Rmis)\n",
+    "    center_2 = R_mis_arr[j]*np.sin(_phi_Rmis)\n",
+    "\n",
+    "    et_map[j], ex_map[j], radius_map[j], angle_map[j] = getTangetial(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
+    "\n",
+    "    kappa_radial[j], gammat_radial[j] = getRadial(radius_map[j],r_bins,\n",
+    "                                                  angle_map[j],phi_bins,kappa_map,et_map[j])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "22ba0469",
+   "metadata": {},
+   "outputs": [
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e9ixHGUx1xyFMzc8qf7979NnJW17s1ClomUBrTgbSrFlpCllac6MQfiYz7cE0yksHbTV5mPbsrQdJ3g+uc9iUyUO1sb6qSGBXQthTK31vZIFhlVyVJ7FDIkJAFqimFipMYotDqJgrjKkOc+kD+sXFjz5g7Uu89vIpp079qILe7hDaCVcFJtYJVllCeANTKrnJVMlgug8L7rQ1d0+La91tIRrlpZHF3WJv5bXro5o4ip00+akDa2t9aBXLFMne21MrAqwAaiA5MpARQMTAmrdQRQa5Ly5qQkVdSp5S6yPiq1TKL8wMUphYQS1Q9Ve/WGsNFsSp/N0+gLdQ+TDOzu6keGk1JxuWYiWCQ0guhDuruwCTD9+Wl66xuGvtzYNk+2srz4CgbZZS3qhTrXZd1cp+Du2rlbXPfGlBiCA5aSsKTJiC9KMhgxEBpAJVOeFuKUqFVK3vLEID22sgkk5jyjK98+51eXbo3ChNP0ylPkSdrFTg1UnKBK3VTWQwmTL1XSnnYfLh21vcrJdEXVKlW0Cy7TVDkR5IKxdcAGuzPrLBgVrJj68WGHy+ArUBPekvn8IWKu2sLSpiX8LylFkf36ZSJUdZMB91y/hlkJ3q1daorTqnVDa3eB/EJ23VmdUdYsJdlBBu5QGvTpdg6vPSJYvr7e0WkGyZyvAJwEHEmpvOgEXdOrms1VjdVq1CMoWq/FIGglbW28qQlgU2UEVg1a/nLyHfs740Gp7QLX2OKk20nVqUjtbsa029Mllxs0xe36iT9s2p1RlIB23J2WMK+SxM97Ts5CYByQfva+3tHEhhc5aK5XG1Og+PnKl9sGwXJ+2lRehtcKBWmeRyLIPMAMuQXGWQBehn9qDSE85R7S9zLSUAMOuDAbyjUsX2YmxyVIHJL53tba7HM5h6y3OtOkRGcB3ARZn0IRBJbvKqdA1Mo7x0zuJG9vYhINlSMxQDZRjwpqU3ACs4sDYwVddBthPqtjcgecAIgfTkG1jJTm2AddpaKYGnanm9UlUbvEGlus/3wZx4cJGC+7uaScJ8bvLqFNCUCXwQtxLBISQ8xAUP8dTUmnqYZH3dwDSyuBn8QfZ2LUiyb+gUykbZMVBafh6swHK51A5YXqkoY9NFQ5ldxdxAEhULaC2wqBMRMkSm5ffUP4xWVKhW+X4GA4XQnHxKCXxGpcpi3TuWm3YKm/1cmRUqcjChAcsKmaZO05QwxVyy0n1ccYgCkynTYzzhjlYHUAvT1upSsbhqdfuq9GOBZMsEVSg2/ypAdS0/3zFsYJkC2b9IA6lTo40NZi7dMZKpCJm41qMSF9gEi4AcGLTKoPkNVAGgSRlf5aQBXZ4yCdmpnHvbAyD2mbkZuDf8XLC/yx0HU6pyYyAN9pFBU27U6TCt1eriKjD5EE4uN7kywX04NeFb1Km1uD1VOmdvI5AuQeQXVSjAWvLsFYpQ7bDPUfrMxC1YVMO5dbMZaEW5tFoOglgbAZRrYDcLDCB5j6r1yRxpHVQAeBUracoJrHlK6SdSyzqnUo3VZRSpGgVzhajJS/Zsd5PqwnhRp5hxmBJmrYDfxwX3ccEhrHgIJzzEpclNT+F4ESazuL3g7VXpxwbJlkn+9QLSVyZlA2Khgg0UtbtigQYPo1heA5aqVA+WdQizAZRRBuuZWoFkyAvpyaoqVeHCHlT+mTUAj1pu1/Tv+Wr5pSl9CMPWnQfJq9M06dAUhekQEu6jjCAwu7sPCx7DqcBU7e5U1i0v9RY3X2Fvt4B0CSK/THAKZZ1yDKdaamVgyQfST8Z6BS+VKnpRI33Pg9V0y7h8JYDJnAhBh8hkAiiRwuXAIpR+vwwUxSl5Cx1UzBrSJ9C6gvsWoFqcV6nmyuEi1/qzcxf8LTORG0TnM5O/z91U1SlO2tk7JdxNK+6mFfeTQPQQT3gMJzzqs4fJt+h6mEYWd9ixt58KpAKU2IQDKrBr7SlcQRSlUa0AV/wj+MKnBPMKls9WPrR7wHJRprodWgBtnoOUfzJRUSmvVaSwIEZX+IySp7z1UXvwmsV1t1QwgWGW8nYXyN1EkV3LTtUpJkxTwjwl3JUgvmiLbnFhfNnA5EP4nsXNdNnefiqQbJkoqnzYEBFnY165mOp6Ua0Cl9qht7wS0s+AFVCGBpPLURQYwbKVFkm9UpVnBBCNUhXqIcpqORwrEGZ9eyrlnpu7lfaLVyavUC6M88TAxAiTWJ2E79TkJisRiDod8RhOG5gMKA+TqNNYlXp7uwTSx0Dkl4ki14tlrXbDDAQdmNbXpnKrWpa7ejvctv7GYBVLDEBI9qytPrVSDiRXNQWWA1WAAki9NlAo3TpByGjBAAQes77MpYywqU+Z7bG2KMp2B5616sz21Opyub2rWp2qU9QygVndw7TgcVKYzObOwGTKZBZ3jSrt2dtPAZItUwhZlYlqKcrDpU1uy1GlCW4jEAAN8jVrCTQKqqrOObBIR51kVaxMAAVSBWO1uKpWHGoBNCxApgCsNsIwIyNWC+RYs880lRahqBYDKWF37LmfFP/CALs2N/FAnRLupoR7hel+qjb3ahKQPEyPDqoDkg6ey5vg3avS3xRItkxRm9psdrcHV9CcVFp9ul2VyKyyUS3Wa/eygmVQMWqRM1PNVQpWscIgYHGAzNxmamXKppZjYZ0pIBAhLHmTq0oWKnkqgNgVP51K2b71M93D9iObGRk6x7uFcHkgMmgWdTpMCQcN4PdxwVM84SGe8Cqeh+melo3FeVWar8hJfwyQkir5FGPW46QgXYCLgrxf4ApA33EMoFEtzjpbS2nhUWkZGnAhKViplhooV8AQSLKVqpXMqc4IoVpPWKz+GkoMHLUAPRxmfRuVsnJD7mpbcD/Qg+2zk9mdqtM8SxC/n6Qa/jhJncnD9Dq+LyA1ZQJKxeIuqdIfG6Tk44AuUwxZC+Pyyw2mChi2gPVwmSoxaYhtVasoWbE6Z4fF7hQsnVqxhPUClFOrVWtell1cE16skAUwOKiYxf5UdShncIjV+tT+miVrhrKqed/9EsYg5UnsjmbLTWuxulfzEa+mE56mI17FI17HlwJTyU60FIsToKoqzQbQ3wBII4DKoVKtn6aYGpiyKtIWqD31YlUgVLi4g0tDd1EyUy0tO7AVOXkHrAKUC+krK1yAHy1ZrVAPbtgqFbKoR7G+RBuVKnZnd13oLG87mkAeOQI8MzBnqTnNCXfzisf5hFfzEU/TEU8FpBamJzo1MAlQ3KjSTGGTk3qQ/hgQZfBw+zTHjNwAVQEq2zEGLGcqfYBn4dIallkdIvRffQ3mJaCTfD5FyVgGFgeAorQEpf+OtFVolySRrlvmAkAyh7qNIQyuvtRko+iA8SqlJQVyIJXF3WQpa37KkygUz6pOc8L9vOJxFmV60sz06fQer87AdEepWNyMfVX6qUC6BaLcjeeZplB3yz1IA8A8XDJBSQfaNXBp9qqtQlTVUpBI9/FglX4/zVpYqw16mMoQEq1VIdS6TID+PrM+ZrXgDB7NgpfN8rLkLXf8fAdw1op4ngFMok6HecXDvOBpPuFxOuH1/IJPphe8ii/4LD7jMRzxSXipIbxkJrG4Qxe6f0qQRhBdA5B8tu43zVH+RRowXpVuBYwZyDlUuALAOWhXjiqNweVVq1ijvo41Q8FahwZWqrmLo6hVsFZWo1byHAODT+7A0LYAKsXNSYBxKlXVySmYLptywaQKNWfQIWM+rHg4LGJ10xGfze/x6fQen07P+Cw+43V4wVM4ikLRqcLUqdJM4ScB6UMBSr1Sd/tMh5B0YwWnB8nAuQawHLhVLOZqjUE/O4LLWSAYgF7IS0nBSQrWpGCtLVhBbbBUqBWqOhogONUSqEppIGVt1Qk4m5EIrgumXohB5fdlhSkfGJhZrO6w4OlwwieHF3x2eI9Pphd8Gt/jdXjRx3u1ugV3lHCvFudVaUZsAvfHgnQNRJcAGioUBgqVe1BAzXbm7jX2Acs57KqXDACgLVzZ1qnYn6gVS23LWn1Jbc6sMZHCBITS5dGqVVQliYMbP0ojtLO+5KrnlqNSGipUNnWaGXxg0F3C4W7F42HB6/mIT+cXfDY944vpHT6Npk7v1erM5riokg/dpkofA1IP0ccClPrPd/tPB60KZg4NRPbcQzZSMQ+Y7CtBP2Vq1ItjdmG+PrPbz+AyoIolTgQk1/JTmOwSJ5pIx0Q5qEytokFF5QqU5qoNbc0JVAmIuahUGYFQWnx6AM3yJrnGMM9id/NhxePdCZ/cveDzu2d8cXiHz2eB6cvpLV4HUaknWnFPCXdOlXp7+1CQzkF0DqBb4enfB4DpUBQqN7DIs3Vm0AayoligfRWLLXgFsNB+xtTLrJFzGMLFUaGaGJQkpFMCKMoozwLWIhYUIhAiFeUKWiuSIQsAaLIjiaDgUJrF4nIGVivBcwnmpWygd+oymPJdBt0n3N8veH13xGeH9/hifocvpnf4Ir7Dl9NbfBYkOz3SinvKuKeqSmZvHwqSh+icCu0BdCs8vfHZz50OYRVwyIFUlCrrswfldsguAsaExF69MnLW9T24kipYInBicCKQ3dxoAmilphuEJ0JQtRIrDPAzzwFAsHJCymJxKYGT1jNSqi0+QI5XNJgYfJdxuFvx+v6Iz++e8dXdW3w5v8NX0xt8Ob3FF/EtPqEjHsOKe2LcO1WaKX4QSHsQ3QqQh+dacOr+7TLdhVTBcRXW5FSqBS0NLbG3zAaogVWuOVwAjLTFmKp6Zf2ZCpQ9Q9cpkYBktaoJyCshTNAHCVxqibmMWSKoVolSpSzWp7mptPycQuWJBKYZSHcMekh4ejji8/v3+Pn9W/z88AZfz9/jZ9MP+DK+xetwwhOteFRVuleIBKbrQRpBNALoVng8OJegGVWpbCqJ6S6sBQSDSH6xKlEHmwdNnqkB7ZyaecjmuKNiAJKGegPMXpuC5UzIKbRwpSDPk4R6WklgWuSkh4UQTta8J+SJpSAZAuxeyxOhFDFNoYpKGVTMpcsnz4R0z8gPGfcPCz5/fI+f3b/F14cf8Lfm7/CL+Tt8Gd7hdTjhdUi4J8Kds7dJx6tfAimVc7BVm3MAjeC5FpytMm2/1wisaQr1x+QRULuwOaUCnQGtVzIqaranZI2K6WdSDhvABK6AlMQas4drVdhWAi2iJmEG8kLyPFeFyVOtWwHA5EsJKQN8Aqck2yxDRUI+AOkeoMcVnz69x9cPb/Cn99/hXzt8i1/M3+Fn8Q0+Cyc8EuOJwsbezoHUQ7QH0K3wXAvNUIW2XeQNF4AqVPkhDTQKkisD9mFdfvEl5dq3Tw9Ur2arZid7XSBSOzTAcg7FHnMmpBREvQyuNYBnscW8BISFEQ6EfDKgNFhPAXnSqieJBQYL5ssiKmVQQUL/eg+kp4yHpyN+/vQWv3z8A/7s7hv86fwH/CL+gE/DgqdAuKOIe5ougjSC6BJAPTyXwNmDpoelB8XOzfB7u+3TfVj0B4RS9MtMZX0EVL9u+4xah/7L7cHWb+9B89tSDg1kqwLFTFhSKIClFBxcAXkl8BKQVlmnEyHfEdKREA9AvlPAplgu1pyYEdYELCv4/Qt4XUFrkqvbD4T0wMCrBT//5C3+/Okb/MX9b/Hn8+/wi+kNvggrnijgjqaSk0YgJc5DFfIAjeA5B45BswdMD0sPykiJ8gCw0f7THUmGmql+tTRQoOF7A6j89ksqd0nBDLY90Fb2qqVwGVC6vibdngLWNSCniLwS8kmewzEg3RPSCyHdyUPskHBHhENi0LqCTifwsopiESHdActrxqefPePvfPJ7/NuPv8K/efg1/mR6g88C8EgT7mjegORVqAfIq88ePNdA08QTD1J3LntIRiCd227nzC/T7CzPdtiDCwAynQGs+VdwHrw9ex2p3EjFPGwerJVjsUyDbEkRiQlrijitUUBbA9Y1Ip8i1lNAOgasLwHTAyE9ENb7gDQfAAIOOYNeXsBv34GXBQjA8kTgL474iy9+j3/39b/E37v/V/iT+IwvotjbhFhA6iHyABk83rL2wOmB2YOlPd77QPnj3C/nILJzNVqme51rsPwA8iG9hevaL+XtEzgD2mD7Hny92nk77JUsOQVbcyignVJEYgFsyQGndcJpjVjWiOU0IZ0iji8Ry3PA/IqwPgWkuzs8RcLDcQHev4CPJ3AgHD9n/MnX3+EfffF/4N97+D/x59MJn4a7AlLijMQZK9IGoAU8BKeHpih414OxB4k/D8MAvQPBHlTnftbeMs0K1Dz6xdRXIHZ+Oe3/0g1sG9kdwGjvjYArB7wFsFU3Kq8zBywcCnALB6w5YuWAU5pwyhFLjjiuE17WCe9PM47HCcf3M06fTzh9GnB6fQeOX+HxtCD//huku4jllyf8h3/yv+IfP/0l/vZEeKAH/X6MYz4hI2NhgWhReBYHTbJ/DPDfuQcobI5ZGx/OH9vRMe2XvAPZhy5tKNdlHt47TP+YAWR+2YS37uWt/0ouAtgdfGAMX7aT2MBGWDhiZYUqR5zyhOf1gHfLAW+Od3jzfI/vvr7H+69nfP7FL/HFf8N4/1XEf/T3/kf8J5/9D/g63iEx4y0fceSMEzMWBhYIvPa7ksKTOeh6aL532lXxj4emOX4/MkD9Mpml9dYGbFsD82aPwWItxY/84tceoLL/md83aqHsnVBRNLHGI094Tgf88Lfv8f3ygL/+B5/hn/39P0Oegf/4s3+K36UDfrUGvPCMBMLCU1EfoB6D/m+5JeT+/2EJ7iY+9F/8739/UAP9//4Scf5rR2pLc8G1h/x79c6U47t+28WV9zqJ1z/57h/iv/5P/xG++bsR67/zFn/65ff42cNbvJ5kvHi930pC0M/b77O7Ftj66O8I3feOwxKjzgVx7u/f+dxwX7p+X6A9lv0yHS5Y2If+4GuXS3/MCJz+9w4BKScsb7bv3dfED70NqBcEAMC3mfFfvfs7+Cf/3X+Af+uf/QGf/E8nfPsPf4Ff/xuv8M9/sSJ+uuDx6QVPdyc8zotczBkXmdpQb0VmM/vK79WbUrv1Ah7a9f7v3EJX9+nf2z2Gfr/u7XMwXgJ5uqfl7A63LtdAtgfRLf9ae3D8NoOlrKO9L24/3Y2MkAw65DaWobYZGS+84jcp4799/6/jP/9X/z6e/i8x/vyb3+Hzfzrh8OYL/PBnE16+mvDuszu8eZUQHlcc7lYc5hV3s1xCdTeten+WXCZhnSgj6NUtApetGzgteP4YlNcdeP7Yhu54Nu+dgXJvHwCIgyHAft/Syrt1uWQ5oy8jn7v8L2gEiV/3sAD+YHqIZMIteX98/f9oDBIgLbWFE97ygl+tE/7n4y/xX37zd/Ev/vorfPGtztfJDPz2GzzFgLB8gue3M16+DDh9ErA+TTg+ZbzcJYS7hDgnzLPMazBPNnV0bu8dTHLLskCsoKn1kvyD2L5uofPHZQ8+OUb7yleO/xkQ+/NTzgNLR/c0CuOj5ZIn7wF2SYK3MA0AGgAj23W/ATj19fia/9H4I6sbvfCK73PCr9Md/rfj38J//+Yv8Je//xrT72bMzyzXCE4T+P170Dff4T4EhPUJ8ThjeiacXhPWp4j1ISA9TFjuMpY54+WQEPWKmGnS+97ZLMB269cgWS7ojYMCuIAWduGqgNk2f+w9dP4Y9+Btjr+dO74ewOmwUyJoPnAm54xAGssn7+7TflkevG/vda+xhUd+1/Za/3NXjFh/2pEXvHDC95nx6/SIvzr9HP/L8y/xl99/je++fcLDG0I8yfAVzBP4eASe3yN89waHSKD8gLjMiMeA5YWwPBHSe6m8p0MAHyKWOWOZGWFOOgFZkrnKy12ouLkDukEWIOsGlmWxEWh2HG2bHJPzwMnx3Idu7335mXX7VQq1rz6XYdrK51idemiabeU96raPZ7EdXSkin++LqLnY25FXvOOMNzngd/kJ//z0Ff7q+DX+6u1X+PX3r0E/zJiegbAoUNMks8EsC/jdM8IUMRMBDFCaEJaAcCKsj4T1RIgHHTs1E/KBkeeAPDHWKSJM2U01zeXm1T1gBJRbnxlEHjKzwh40O1djqNrt/pwF2gI0slG/PvW5ZLTsAnUGltHnQrPvYFt5r0Lg4ZHveR4ged6HCKggSTU74YUT3mTGG57wu/SE/3v5HP/y9BX+6t3P8Ku3n+L9m3tMz4R4hFwCT4QQAjhG8LoCpxPw7j1CCJgBEN8hrBPCGhEWIJwI6V6e8x0hHWSYcj4weBKwMGWkyEgGF7G7M7q2Bh1gRNLQsO0eIPJA7YBm588r2Baorbq172/hmuYLgayemGvUqP/M+L3Y7HM9PLJPaD53ywQRPUgLZ7xwxjMD3+UDvklP+PX6Kf769CX+xfsv8Zv3r/Hd2wfwcxSgTlxvMBkjyIBKCTgegSmCogKeAWQgpICwBqQFWBdCWiDjsQ5AXqBDiRk8ycUXOQYgyoQbFDPWAISQ9cbWVb0IKICRg8ogow6oPcjkOJ8HDYhXw7YBqp70Uf1nsB/t73MJHNnHbb8BIFm/DBHQgpSYsSDhyBkvzHiXA97wjG/TK/x2fY3/Z/kcvzp+ht+8vMY37x5xej4gPgeEExAWCCgBQAwClV26rkpF72P5O+Si0QmUgHUlucp5gQyRWXRw3wHIK2Q48szIOq8UT9qajApZkElfV7LbobF7iLoIWBUes8lwJWRyTKuawX3W3qvbDKTQvDeNcoxfemBG+/U3a7oFHr/90t2Obp1c1A8bWTiVDtsXznhh4Jkj3uQDvsuP+O36Gr9ZP8VvT6/x2+MrfPv+Ee/e34FfIuKREE9id0WhQgACoUypmDP4tABBVCoQlT+eGKAcQDkgJLnkK606hDgBZMOSV7myi6OoFU92OzQAkWWeh8BACAhRgBC4gkzIRlyeR4B5m+wBk+N7HjI5b7Y9DkGb5p1upUvQbE96v/95eOQz5wGS9dsgArbjjxZOSODSeXtk4B1PBaZv1lf4/foJfr+8xu9Or/CH4yN+eLnD8jIhvASEo1zsQAl2uxkJ5iGWS7DK1cXLCTgGmetTx6gTA8jRzc0gapVXvZhiBrJdXzhD5pdKBF7kYgrWuzCUe+0FNHCVexYTF2tcHVweoB6wQHxWxeRP7QDrWop++3SL2tST3H9mDM/mvR2A+vc+dJrj0UC2BZKVFmYsAN7lgCNH/MB3eJPv8c36Ct+mV/j98gq/P77Ct8cnfP9yj5eXuahTWCC3BUkA7O7vgUBqe0hJZ5bJMqozLnort9oKnaBKxUHVCkhZriNMNgHIDLkETC/3ynpBKzdXQ+stZhPB7qrOQSZ/ywqWh8urVgiMNTuAQkYgXAQM7rWpWN0W6joY06hlVU9su0QM9tlRH/n8dQDJ6w+DCNgfEblwxgIuqvTCES8c8Sbf44d8j+/So8L0Gt8sT/jD6QE/HO/xfDxgPU6gU5BW2ioP0pn36mTq1Nhema1lWWUCsxgBsz9bGJLDOCDolVqURaFykgsmyBRrVbCihvbQggWd4wGECleU2ZM9XASU3EUGUGABWwGyluMeYHKuz1slAEz+NlfNCe3hGAB3DiBg38bk9eDnfeA1/KOhtV6VXpgKTM/5rsD0fXrC9+sjvlse8f3ygDfLPd4eDzgdJ/AxIp5Iruczu8uoHamkIFFoJ+DIWS+5iuBFlKq5qSTL1IzEolB2K1tRKQbNOmfDrNcQqhVyUrDsymeDKhLkPnz6OmnmCmKPFAQ4CiSQQeBqwCJGUrg8NHuAAdhVsWm+oDrlZF+AB7hdheQzHwYR0A70t5xkQ2xtoNsLi8W98IR3fMCb/IAf0j2+T0/4dn3CH9ZHfLc84IfTPd6eDng5zVhPEbSEBqaQ0PbKm0LFIDlGW3tlJpd1BcnZkNligMYCAQBqf+Vqd5saMsmMMzlZSHdgmWJlyFXTRbUgVzEEs0KCTMGNIVwGVHbW2ENm6nUOMNj7sAx1BTwCw7767O0j2z4eImAfJG9vNtx2gQy3PSlM73jGu3yHZ77DD+keb/IDvk8P+GG9F1Va7vC8HPB8PGA5TeBTRFgIZDBp645s7gNbiCC3+pArkP0UQCASG1TrIwMQLkqwBnYO2hKEwkVl2m1WG8Sk855Zxoool9LbdEdmiWLDXOEiKlAhQG/0xAo715s4SchrrNGDdgkwQEpxAwguq8/efiOA5PMfNhJx71r+0cD/fvjtiylTD9P6iDfpHj+sD/h+uce79YB3pwNOy4S0BECvNg4raXaqj/qHUvtwi7X4OMitQ3hdS0iHlhP6o0FMej8du1mlPGediI2SWqDeYYRNsRQsMhtMdcI1BJSHKJWoFnRK7iFcJL8zKFwVpqpe2cElh6ICNgkEHw6QbP9xIQKuB6m/COCFAxYYTDOe8x3e5Tu8y2J3b9M93qY7vFkFpOf1gOdlxnGNWJYIXoLCJBNulLmoLD/5DKWQsOaozfycSSddX6nZvx43/VHMQNazrkplimVqxREyUZspVXSKZXNh6ZRGnO3SeuisyRirFvnXEBUj1rkbBCKQz12EnLfq5QGb+kp0v9yiQvJzPm5M9DmQyrqG7gzgxHJNm7e4F57wwjNe1Oo8TN+vD/hhfcAPyz3ermJ1708zTqcJeQnAKtmJTJkcTPXWZlSfu5aeLTZRGackGcpgUkWjpdpfZinXFPsrQKn1ZW396W1NbF4qAyszdOpInfYocJ03neocpWw3CfCqxQCSWqJaYw8XBWlIFLh2rBHQVp5fblUh4OMhAq4HaaRK3uIWVaYepud8wBtVp3fpgOd1xvt1xss64bROWNeqTrQ6u7OpGDNvoSotPdrmKFuYwSmL9VECBTmSFtJBcrmE9egAeqGCqaE+KEu/Hxgyo1+u9SmbtS9rSYKCA8tylU1+a4Hd7FABY9b1DC1D2N+ILVyqbpwrXAbW9CEAAT8ORMA+SPLe+Arb1AXvBUGBqsr0kg94lw94znd4zodide/ToVjd+2XGcZmwLLGoE9lksA4kU4xhv7kGc1iLztlec0PHlMReVtI8pYFdf0yBqlgrSa5imZo766zJXq3kRg82GZv8AFOmAlYUAKsFUpkf1OyQrfJhqkWAzN+tOSujBHuZa34LlynX5I/N3wREwD5IAIZX29oFkyeXl3plesmSn97kezynO7xd7/A+zQWml3XGUa8cTimA11AmLKtzeLbq5BdW+ypHjMLG9urOXLtmXGvPalQbqPRVhpzDolJMMnEGUwWIGVmDPLLLV2EAVrAyAsqtUaBVdqaBapmUooPJwr2HS5+nPxZEwHUg2es9VUrO4hYOOEGuizOgPEzP+U5gSnd4nw94t97heT3gmCYcU8RxjTK/gbbsoDCFlQb5CbUfzxafoWzZyVJl35TBlEF6lySiWqMCWqiICXmW408ZMqm+2Z+qGLOqVQQCV7VqblGrsCFW2+vBInJ26BQMap3lpubFFrtwr8+NQtnyY9+56GNBGqnSohdknhDxkmdndQ6mfMBzPuB9OuB9mvGSJrykqVjdukakNYLXAOj01GGjTr6Fp1/CL8HyE1XF6Vt7QFUpln4Wub9NBpJc9lmUSqvqGQBYK+xZwAoMYNafzaS259RKW4NlTtLo4GKUW5z0YJFlJpezKKMN8V61StjrtlOdWvJHhwi4HSQAZ1UpMTUwvfCMk7O6DUwKkj1e0oxjmnBKEUuKMr3PSkCxOupAqvmJekAstAKtUg0dr6qUqFGoJYWiXPLB1v7kLjVBvUvu8SfDiMECjoCKolasoT1H2QdBFS1qZuIKGYIL6rm+7+/GWu5BrVmq3OG+BHfbX/LW9MdSI1nfggRgV5WsHJA6i1s4YtEAXoBSmMp6atXJrO5lnbCY1aWok9wrTK6g2CoTiu1tlgKVHke7xKpUzblaoo5IKLf+oAyCXMZW4or+TDufBSoEmR1Z1hQodGCJMon9afeM9v0FRrW5oEyYYhlYGtosrPucBXfDcgGJy/14LEeBMba8D1munWz93OxsvSqZxWUFymCSzOSAcjA9J1GnY56cMokqHdcJq6qTzWQHr0yd1fnsNBzY6ksHSO6fL6rtKUxFpUJorS9QCevFMpPotUHFbJfPyu26M5MAkqHKxOVZakuqVgFlW7n3juaqAhh7sCS3GVhmdcRqyXlrh0W1NF99FFCX7h2yN93xnr31qtRb3AmxUaeXLEB5mI6sIGWfm6rVnVa1uhxEnXJnd/olvO3J2UEZC7VZfMFSoWgPilMpoPb1kSgZAwLbWpXKPwMGlqlRKHPxh06pijrpOlgVyeB229g9zoLl6S6KhVoEdar1QUD9VCD5SbfM4mS9wlTUKdfc9MIzjnkus6UcsyjTKU845QlLjhUmm3fTslOTm6gcWHQqVZZRtRworbWSo0LY3IRoo1Jmi5apAO23q+UED5UsqlKot8EFSCGSD3B0qtUoEqtyUWN/Z8EyWDRnIbgvZXCRQUfXA3XNTfnOTcC+Z28eJgvevcUtPOHEEQviLkzP+YCXPBerk7wktabjOkkI17k2izrp7T1Qho30yoRS0NyEcqCqTgfXph7VdR7LgcnSeWzWBy0dJC2QrijbOAPtjAEOqix3JbUGaFDry1Ehi2jVSsHK0e5liE1O3IDFDizmtuWnIJkdXgTqxwAJuE6VzOIy00WYTmp7x6xgZWvNSX465VgeSw4uiFd1Qsa+1TUwyd9mz26SZMlAwVpr8k+eiHdtz6tUY32UpZQAVDAzVRucxlDJ1NsiHQZQNsWKkqVyZAFN1QqstugDuVcpp1x7YFHuSg5S+xgDdc3Nim8FCQWgLUwWvKvVxTKBl8H0kg+uVDDhmLWYqapUHwLRS5qxZAngp7WqU0qhbdklO59t666xO3v0y06Hej3nzvacShWoYqwB3QRNxo/oqtpoogKVrNtxD/afHHe9RCmw7CswqWpFLhmsUStXdmhUytapwtSGO92/2J18nQLUtRAB14Nkry+pkllcn5cKUDxtYHrRZwPp5B9JLO64ShBfUyxzltu9YYo66VgjZNTWnB1MWx8tmxpUkI64QCidZZu7rHfh3MoIRPJZJulILvvXHAU4VUSsUGml0dwowz5AQGQE2EhSA2mrVqVoy60NemUqVfVNq6EFa/pYkPz2UU6yffeCt8w7KRaXOdwEU1WnWbtTBKCXMhmrzFOeSnaicoNHKs8DVXIjC0pRc0+l+sWr1hkF2wT0jGp9bFV0DfxAsVDpokkVqsl11kTNzFHrTAUwqVMJXFWVzqlVA5NXJ1+2HIA1tLwPAQm4zt68KqVOmVKfm66FqahULK26RZWpBPFGnWoLz+AatuzKv9xdLuri+uVKjgK2tterFNAG9NSeq/Ljk/7sFSBE7EKlHxbFIgTUISxFvYq9bdXKwrXVs7xabzKVLQ6sAtSlGxhfAsleZ7fvtRbn81JGKDBZp6+HackCmUG0cCi56ZTF6uyWHWuy3ERVnczmvCp1EPlgXk7oXobyDwC+uHlpGQZ0tT4ZNaf+k+VLFfvLBOnlG0DFJOsrdKiC9bcoXFwtsFcrXzrY2CDVY1TAsu3lDwKmHxMk29+DBGyDd29xmUPTkvPq5AP4kicctaVnUPncdEquVae35Mg5yE0cTZ1YSgXtMNvu4extt0o+WkrZ4EyO2lMpYGt9qVUpoLO/HqpgMGVQJGTIeplPYJVcZRZY1Ep+u/x0Z3GNDQbahnX9iAfLKVR71K4FSd6/TpXa3HQbTC9auDSrM5CODUhidWZ3cncqp052k8a8tbthv12Xm4a1KKDNSoFagdLAvrnTup3GTqUa69MaUhn+Yr2/uf4C0t5fttFsq6iVaJOVFeyXVYWx8kILUgV9W6PiUhposlMX2qdbQAK2Ock+M1KlvraUClQ1LyUOV8O0ZMlEa444Jq2AZ5m4vtwsSK0uM7kipstOZnGd3RWrcwG82JwdUNRtrDZHXpWa2pLLUaNlR6Xqe9X6GO0tnHzLD4DUpya0UMXQ5GjmCpGOeThvgWGgVuUHUQXJw0VN2WALEnCdvcln9lXJYPJ5qX8+B9NS7nRQQ/jCQWCybhW1OgPLt+rqHdZRq+JdVqotPDQtu2F26hbp4NWTa8HcltEoTrM9+/xIpcz6TKpMMvR+fQ1UREBiEJxSaUi3811+NVBGJ8jt4QcWeE6tghybxgadSk23gGRfc2Rv5b0zFjeCyIfwTWbSx1GDuDwshE9YcxhYnQBld/ssN7vOPozX5xYiNDZ3ttulX/pgbqMcE+/b3qjT2FQu6ui4HGopISXZroGdsl48kMy8whCqYk3NTCibgpJuZ+kYPqNWVZ2cDeq26RaQgNtVaZSXPEQG1wimF7fuC5irWp+VCOo98uzm13JPYnYtOzC2Ntdnpx4sf/j3mOoH1V2qnu8szAx/zV4J6GZ9KYFjFCXzv8591T2o6rr9cAjwOgjP5ypp7TnA9tQqYGuD5DLULbcevaRKo7w0gslnqRNPjSr16rSy2NviSgSrZiYpYNaKeLIbXG/USdedKgHe+rr8xHybOvk8lXE+R5ntnVEpDgEEaxWizVMW0nP+MKjcp9jlqgKHHYsC0latbBBescEATJdugtzfirRXJQAbmKwkYHdd8uE7cdiFaU+drDVnxUtTqKJOdv9hVpvrs5NFkaY8QFuFamByx5675wIFWnVqzpc7zWZjZ1p7wFal9MSISqn1yTPXXBalzkQpfzBUojoOJmeBZIHdCpm9Wrn8VC3vBnsr6xcsrr87Uw9TVastTF6dTJUWrjdUXLnC5IO45Cbq1MmyUg3jvpA5evQZargYTD0AQcZ9l48Fqgdu8zOuVClvfVoKIDu5GtLL0GM+n6k8VAWW8vUqTHb5u9wp3pRbs5JBaGqlMY0ImPbKAEC1N9l2XpVGeWnTorORlx1M/eMlz6U8UEHSkgHHMrbJ7jFcg7iqU/LqRE6ZqOYkl6N6hZKDjRamvdGaQLU7X4OyYJ62Lb/hVTG6NCqllja0vgDXMpR/CUWlFC7KeR8qhWmb+FSpgq6DO5Dq8OKRWk3X2FtZd6oEfd2XBPq8NIJJIAtDmKzWZC06s7tV109J7sZZ7ojugrgUMUNXJkApFVSYahhtSgY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+      ],
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "R_mis_ind = 10\n",
+    "plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map[R_mis_ind],ex_map[R_mis_ind],\n",
+    "                       kappa_radial[R_mis_ind],gammat_radial[R_mis_ind],r_bins)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2dbde4d3",
+   "metadata": {},
+   "source": [
+    "Finally we can plot the lensing profiles for the whole miscentering distrubtion"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "7e458c10",
+   "metadata": {},
+   "outputs": [
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+      "text/plain": [
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+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for i in range(N_R_mis):\n",
+    "    plt.plot(r_bins_mid,kappa_radial[i].mean(axis=-1))\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "2864956a",
+   "metadata": {},
+   "outputs": [
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+       " </g>\n",
+       " <defs>\n",
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+       "  </clipPath>\n",
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+       "</svg>\n"
+      ],
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for i in range(N_R_mis):\n",
+    "    plt.plot(r_bins_mid,gammat_radial[i].mean(axis=-1))\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ea9ce0dc",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

From ec1e463551fb14cab8abc37220e6d953be0764d4 Mon Sep 17 00:00:00 2001
From: Chris Davies <cdavies@cosmogw.kosmo.physik.uni-muenchen.de>
Date: Wed, 9 Nov 2022 16:14:14 +0100
Subject: [PATCH 03/14] moved code from modelling.py to utils.py and added
 function descriptions

---
 clmm/utils.py | 246 ++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 246 insertions(+)

diff --git a/clmm/utils.py b/clmm/utils.py
index 3f24affc9..a9e774fe1 100644
--- a/clmm/utils.py
+++ b/clmm/utils.py
@@ -7,7 +7,253 @@
 from scipy.integrate import quad, cumulative_trapezoid, simps
 from scipy.interpolate import interp1d
 from .constants import Constants as const
+import matplotlib.pyplot as plt
+
+from astropy.cosmology import LambdaCDM #update
+from astropy import constants as astconst #update
+
+class profiles:
+    '''A class to generate 2D covnergence profiles on a regular grid
+    ''' 
+    def __init__(self,M,c,z_l,z_s,sig=False):
+        
+        self.M = M
+        self.c = c
+        self.z_l = z_l
+        self.z_s = z_s
+        self.sig = sig
+        
+        self.cosmology()
+        
+        return
+    
+    def cosmology(self, H_0 = 70., Omega_m = 0.3, Omega_Lambda = 0.7, Tcmb0=2.725):
+        
+        self.H_0 = H_0
+        self.Omega_m = Omega_m
+        self.Tcmb0 = Tcmb0
+        self.Omega_Lambda = Omega_Lambda
+        
+        return
+        
+        
+    def get_r_vals(self,nbins,lower_r,upper_r,log=False):
+        '''create radial bins for profiles
+        nbins: number of bins
+        lower_r: lowest bin value
+        upper_r: highest bin value
+        returns bin edges in units provided, or kpc if none are provided
+        '''
+        #create r values
+        self.nbins = nbins
+        self.lower_r = lower_r
+        self.upper_r = upper_r
+        self.log_r_vals = log
+        
+        
+        if self.log_r_vals:
+            if self.lower_r == 0:
+                raise ValueError('log(lower_r) cannot be evaluated for lower_r = 0')
+                
+            r_vals = np.logspace(np.log10(self.lower_r),np.log10(self.upper_r),self.nbins+1)
+            
+        if not self.log_r_vals:
+            r_vals = np.linspace(self.lower_r,self.upper_r,self.nbins+1)
+        
+        #if no units are provided, set units to kpc, otherwise keep input units
+        r_vals *= u.dimensionless_unscaled
+        if r_vals.unit == u.dimensionless_unscaled:
+            r_vals *= u.kpc
+            
+        self.r_vals = r_vals
+        return self.r_vals
+    
+    def kappa_NFW(self,r_vals=None):
+        '''r_vals: radial bin values for halo lensing profile
+           M: halo mass
+           c: concentration
+           z_l: lens redshift
+           z_s: source redshift
+           delta_sig: If False, return convergence profile, if True, return delta Sigma profile
+        '''
+        
+        if np.all(r_vals.value) == None:
+            r_vals = self.r_vals
+        
+        cosmo = LambdaCDM(H0=self.H_0, Om0=self.Omega_m, Ode0=self.Omega_Lambda, Tcmb0=self.Tcmb0)
+
+        r_200 = ( (astconst.G * self.M)/(100. * cosmo.H(self.z_l)**2) )**(1./3.)
+        r_s = r_200 * self.c
+        delta_c = (200./3.) * ( self.c**3 / ( np.log(1+self.c) - ( self.c/(1+self.c) ) ) )
+        
+        x = r_vals/r_s
+
+        Sigma_crit_coeff = astconst.c**2 / (4. * np.pi * astconst.G)
+
+        D_s = cosmo.angular_diameter_distance(self.z_s)  
+        D_d = cosmo.angular_diameter_distance(self.z_l)  
+        D_ds = cosmo.angular_diameter_distance_z1z2(self.z_l,self.z_s)  
+
+        Sigma_crit = Sigma_crit_coeff * D_s / (D_d * D_ds)
+
+        k_s = cosmo.critical_density(self.z_l) * delta_c * r_s
+
+        coeff = 2.*k_s / (x**2 - 1.)
+
+        f_internal = 1. - (2./np.lib.scimath.sqrt(1.-x**2)) * np.arctanh(np.lib.scimath.sqrt((1.-x)/(1.+x)))
+
+        nfw = coeff * f_internal
+
+        if self.sig:
+            return nfw.to(astconst.M_sun / u.Mpc**2).real
+        if not self.sig:
+            return (nfw.real / Sigma_crit).decompose()
+
+    def make_grid(self,npix,r_max):
+        '''make 2D grid centered on origin
+        npix: resolution of grid
+        r_max: width of grid is 2*r_max
+        '''
+        
+        npix *= 1j #imaginary so that ogrid knows to interpret npix as array size
+        y,x = np.ogrid[-r_max:r_max:npix,-r_max:r_max:npix]
+        r_2D = np.hypot(y,x)
+        
+        return r_2D
+
+    def kappa_NFW_2D(self,npix,r_max):
+        
+        '''create 2D NFW profile on grid
+        '''
+        
+        self.npix = npix
+        self.r_max = r_max
+        r_2D = self.make_grid(self.npix,self.r_max)
+        
+        return self.kappa_NFW(r_2D)
+
+
+
+def KaiserSquires(Sigma):
+    '''Apply the Kaiser Squires algorithm to a 2D convergence field
+       Returns the complex shear as e1 and e2
+    '''
+    kappa_tilde = np.fft.fft2(Sigma)
+
+    k = np.fft.fftfreq(kappa_tilde.shape[0])
+
+    oper_1  = - 1./(k[:, None]**2 + k[None, :]**2) * (k[:, None]**2 - k[None, :]**2)
+    oper_2  = - 2./(k[:, None]**2 + k[None, :]**2) * k[:, None]*k[None, :]
+
+    oper_1[0, 0] = -1
+    oper_2[0, 0] = -1
+
+    e1_tilde = oper_1*kappa_tilde
+    e2_tilde = oper_2*kappa_tilde
+
+    e1 = np.fft.ifft2(e1_tilde).real
+    e2 = np.fft.ifft2(e2_tilde).real
+
+    return e1, e2
+
+def getTangetial(e1, e2, center, dx=10./1000.):
+    '''Measure the tangential and cross shear maps from the e1 and e2 maps
+       Requires a center as an input, about which the tangential and cross maps are calculated
+    '''
+    n = e1.shape[0]
+
+    xx = np.arange(-n/2, n/2)*dx
+
+    XX, YY = np.meshgrid(xx, xx)
+
+    center_1, center_2 = center
+
+    from_cent_1 = XX - center_1
+    from_cent_2 = YY - center_2
+
+    angle = -np.sign(from_cent_2)*np.arccos(from_cent_1/np.sqrt(from_cent_1**2+from_cent_2**2))
+    radius = np.sqrt(from_cent_1**2+from_cent_2**2)
+
+    angle[np.isnan(angle)] = 0
+
+    et = - e1*np.cos(2*angle) - e2*np.sin(2*angle)
+    ex = + e1*np.sin(2*angle) - e2*np.cos(2*angle)
+
+    return et, ex, radius, angle
+
+def getRadial(radius_map,r_bins,angle_map,phi_bins,kappa_map,et_map):
+    '''Bin a map into radial and angular bins as a 2d histogram
+    '''
+    _N = np.zeros((len(r_bins)-1, len(phi_bins)-1))
+    _K = np.zeros((len(r_bins)-1, len(phi_bins)-1))
+    _GT = np.zeros((len(r_bins)-1, len(phi_bins)-1))
+
+    ii_r = np.digitize(radius_map, r_bins) - 1
+    ii_phi = np.digitize(angle_map, phi_bins) - 1
+    
+    for i_r, i_phi, kk, gg in zip(ii_r.flatten(), ii_phi.flatten(), kappa_map.flatten(), et_map.flatten()):
+
+        _N[i_r, i_phi] += 1
+        _K[i_r, i_phi] += kk
+        _GT[i_r, i_phi] += gg
+
+    kappa_radial = _K/_N
+    gammat_radial = _GT/_N
+    
+    return kappa_radial,gammat_radial
+
+
+def plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map,ex_map,
+                       kappa_radial,gammat_radial,r_bins):
+    '''quickly plot the convergence, e1,e2, ex,et and radial profiles
+    '''
+    fig, ax = plt.subplots(2,3,figsize=[9,6])
+    ax.ravel()
+    
+    ax[0,0].imshow(kappa_map,origin = 'lower')
+    ax[0,0].set_title(r'$\kappa$')
+
+
+    ax[0,1].imshow(e1_map,origin = 'lower')
+    ax[0,1].set_title(r'$e_1$')
+
+
+    ax[0,2].imshow(e2_map,origin = 'lower')
+    ax[0,2].set_title(r'$e_2$')
+
+
+    ax[1,0].imshow(et_map,origin = 'lower')
+    ax[1,0].set_title(r'$e_t$')
+
+
+    ax[1,1].imshow(ex_map,origin = 'lower')
+    ax[1,1].set_title(r'$e_x$')
+
+    
+    
+    r_bins_mid = 0.5 * (r_bins[1:] + r_bins[:-1])
+
+    ax[1,2].plot(r_bins_mid, kappa_radial.mean(axis=-1), label=r'$\kappa(r)$')
+    ax[1,2].plot(r_bins_mid, gammat_radial.mean(axis=-1), label=r'$\gamma_t(r)$')
+    
+    plt.legend()
+    plt.show()
+    
+    fig,ax = plt.subplots(1,2)
+    
+    ax[0].imshow(kappa_radial,origin='lower')
+    ax[1].imshow(gammat_radial,origin='lower')
+    
+    ax[0].set_ylabel('r')
+    ax[0].set_xlabel('$\phi$')
+    
+    ax[1].set_ylabel('r')
+    ax[1].set_xlabel('$\phi$')
+    
+    ax[0].set_title(r'$\kappa$')
+    ax[1].set_title(r'$\gamma_t$')
 
+    plt.show()
 
 def compute_nfw_boost(rvals, rs=1000, b0=0.1) :
     """ Given a list of rvals, and optional rs and b0, return the corresponding boost factor at each rval

From febe795ed5b51e041919a347524ebc7ae3d12345 Mon Sep 17 00:00:00 2001
From: Chris Davies <cdavies@cosmogw.kosmo.physik.uni-muenchen.de>
Date: Wed, 9 Nov 2022 16:15:25 +0100
Subject: [PATCH 04/14] updated notebook to account for code moving from
 modelling.py to utils

---
 examples/demo_modelling.ipynb | 2377 +++++++++++++++++----------------
 1 file changed, 1197 insertions(+), 1180 deletions(-)

diff --git a/examples/demo_modelling.ipynb b/examples/demo_modelling.ipynb
index 06cd1aece..19bdc323e 100644
--- a/examples/demo_modelling.ipynb
+++ b/examples/demo_modelling.ipynb
@@ -13,16 +13,14 @@
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
     "import sys\n",
-    "sys.path.append('/home/cdavies/CLMM/')\n",
+    "#sys.path.append('/home/cdavies/CLMM/')\n",
     "import clmm\n",
     "from clmm import Cosmology\n",
     "from clmm.support import mock_data as mock\n",
     "from clmm.galaxycluster import GalaxyCluster\n",
     "import matplotlib.pyplot as plt\n",
     "\n",
-    "import clmm.utils as u\n",
-    "\n",
-    "from modelling import *"
+    "import clmm.utils as u"
    ]
   },
   {
@@ -42,7 +40,7 @@
     {
      "data": {
       "text/plain": [
-       "'1.0.1'"
+       "'1.4.0'"
       ]
      },
      "execution_count": 2,
@@ -87,6 +85,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from astropy import constants as const #update\n",
+    "from astropy import units as un\n",
+    "\n",
     "#specify parameters for NFW halo\n",
     "c = 1 #concentration\n",
     "z_l = 1.0 #lens redshift\n",
@@ -94,7 +95,7 @@
     "Mass = 1E13 * const.M_sun\n",
     "\n",
     "#define physical size of grid\n",
-    "units = u.mpc\n",
+    "units = un.mpc\n",
     "r_max = 10 * units\n",
     "\n",
     "#number of pixels in grid\n",
@@ -128,7 +129,7 @@
    ],
    "source": [
     "#lensing_map has the option to return either Sigma map or the convergence map.\n",
-    "lensing_map = profiles(Mass, c, z_l, z_s, sig=False) \n",
+    "lensing_map = u.profiles(Mass, c, z_l, z_s, sig=False) \n",
     "#make map\n",
     "kappa_map = lensing_map.kappa_NFW_2D(npix,r_max)"
    ]
@@ -150,7 +151,7 @@
        "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2022-10-06T15:35:29.110446</dc:date>\n",
+       "    <dc:date>2022-11-09T16:03:52.275177</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -181,8 +182,8 @@
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p5ca885bb24)\">\n",
-       "    <image height=\"218\" id=\"image9a993a48e4\" transform=\"scale(1 -1)translate(0 -218)\" width=\"218\" x=\"48.982812\" xlink:href=\"data:image/png;base64,\n",
+       "   <g clip-path=\"url(#p35afa4834e)\">\n",
+       "    <image height=\"218\" id=\"image00e9359b3f\" transform=\"scale(1 -1)translate(0 -218)\" width=\"218\" x=\"48.982812\" xlink:href=\"data:image/png;base64,\n",
        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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
@@ -191,10 +192,10 @@
        "      <defs>\n",
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-       "\" id=\"md86c106647\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"mc249ef2241\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"48.982812\" xlink:href=\"#md86c106647\" y=\"228.439219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"48.982812\" xlink:href=\"#mc249ef2241\" y=\"228.439219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -263,7 +264,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"103.342812\" xlink:href=\"#md86c106647\" y=\"228.439219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"103.342812\" xlink:href=\"#mc249ef2241\" y=\"228.439219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -294,7 +295,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"157.702812\" xlink:href=\"#mc249ef2241\" y=\"228.439219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -307,7 +308,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
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        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -321,7 +322,7 @@
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        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
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        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -472,10 +473,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
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+       "\" id=\"m27e0fa2ff4\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
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        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -490,7 +491,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_7\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"48.982812\" xlink:href=\"#m27e0fa2ff4\" y=\"201.259219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -532,7 +533,7 @@
        "    <g id=\"ytick_3\">\n",
        "     <g id=\"line2d_8\">\n",
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   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "id": "2aaf9cb0",
    "metadata": {},
    "outputs": [],
    "source": [
     "#lensing_map has the option to return either Sigma map or the convergence map.\n",
-    "lensing_map = profiles(Mass, c, z_l, z_s, sig=True) \n",
+    "lensing_map = u.profiles(Mass, c, z_l, z_s, sig=True) \n",
     "#make map\n",
     "Sigma_map = lensing_map.kappa_NFW_2D(npix,r_max)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "id": "72993065",
    "metadata": {},
    "outputs": [
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        "      </defs>\n",
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        "      <g>\n",
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@@ -1162,7 +1163,7 @@
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        "      <g>\n",
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@@ -1176,7 +1177,7 @@
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        "       <path d=\"M 0 0 \n",
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        "      <g>\n",
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@@ -1345,7 +1346,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_7\">\n",
        "      <g>\n",
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        "      </g>\n",
        "     </g>\n",
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@@ -1387,7 +1388,7 @@
        "    <g id=\"ytick_3\">\n",
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@@ -1941,10 +1942,10 @@
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@@ -1979,7 +1980,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 11,
    "id": "eec34ea3",
    "metadata": {},
    "outputs": [
@@ -1987,19 +1988,15 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/cdavies/CLMM_testing/modelling.py:138: RuntimeWarning: divide by zero encountered in true_divide\n",
-      "  oper_1  = - 1./(k[:, None]**2 + k[None, :]**2) * (k[:, None]**2 - k[None, :]**2)\n",
-      "/home/cdavies/CLMM_testing/modelling.py:138: RuntimeWarning: invalid value encountered in multiply\n",
-      "  oper_1  = - 1./(k[:, None]**2 + k[None, :]**2) * (k[:, None]**2 - k[None, :]**2)\n",
-      "/home/cdavies/CLMM_testing/modelling.py:139: RuntimeWarning: divide by zero encountered in true_divide\n",
-      "  oper_2  = - 2./(k[:, None]**2 + k[None, :]**2) * k[:, None]*k[None, :]\n",
-      "/home/cdavies/CLMM_testing/modelling.py:139: RuntimeWarning: invalid value encountered in multiply\n",
-      "  oper_2  = - 2./(k[:, None]**2 + k[None, :]**2) * k[:, None]*k[None, :]\n"
+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:145: RuntimeWarning: divide by zero encountered in true_divide\n",
+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:145: RuntimeWarning: invalid value encountered in multiply\n",
+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:146: RuntimeWarning: divide by zero encountered in true_divide\n",
+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:146: RuntimeWarning: invalid value encountered in multiply\n"
      ]
     }
    ],
    "source": [
-    "e1_map, e2_map = KaiserSquires(kappa_map)"
+    "e1_map, e2_map = u.KaiserSquires(kappa_map)"
    ]
   },
   {
@@ -2012,7 +2009,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 12,
    "id": "2ba6da86",
    "metadata": {},
    "outputs": [
@@ -2027,7 +2024,7 @@
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-       "    <dc:date>2022-10-06T15:35:29.887896</dc:date>\n",
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        "    <dc:creator>\n",
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@@ -2058,8 +2055,8 @@
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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
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        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
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+       "\" id=\"m7fb05967c7\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#mdd746e95a0\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#m7fb05967c7\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -2107,7 +2104,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#mdd746e95a0\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#m7fb05967c7\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -2138,7 +2135,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"118.437344\" xlink:href=\"#m7fb05967c7\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -2179,7 +2176,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#mdd746e95a0\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#m7fb05967c7\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -2228,7 +2225,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#mdd746e95a0\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#m7fb05967c7\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -2264,7 +2261,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"245.843594\" xlink:href=\"#mdd746e95a0\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"245.843594\" xlink:href=\"#m7fb05967c7\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -2310,10 +2307,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L -3.5 0 \n",
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+       "\" id=\"mdd2077d222\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m3a48b02582\" y=\"10.999219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#mdd2077d222\" y=\"10.999219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -2326,7 +2323,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m3a48b02582\" y=\"53.467969\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#mdd2077d222\" y=\"53.467969\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -2341,7 +2338,7 @@
        "    <g id=\"ytick_3\">\n",
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\" y=\"-10.226875\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
@@ -2739,10 +2736,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"mb58c629b79\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"md0b8068baf\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#mb58c629b79\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#md0b8068baf\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -2778,7 +2775,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#mb58c629b79\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#md0b8068baf\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -2809,7 +2806,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"118.437344\" xlink:href=\"#mb58c629b79\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"118.437344\" xlink:href=\"#md0b8068baf\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -2850,7 +2847,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#mb58c629b79\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#md0b8068baf\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -2899,7 +2896,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#mb58c629b79\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#md0b8068baf\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -2935,7 +2932,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"245.843594\" xlink:href=\"#md0b8068baf\" y=\"228.226875\"/>\n",
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@@ -3012,7 +3009,7 @@
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        "   </g>\n",
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@@ -3293,10 +3290,10 @@
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        " <defs>\n",
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-       "  <clipPath id=\"pad4e989ea7\">\n",
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@@ -3342,7 +3339,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 14,
    "id": "6b8c1825",
    "metadata": {},
    "outputs": [
@@ -3350,18 +3347,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/cdavies/CLMM_testing/modelling.py:165: RuntimeWarning: invalid value encountered in true_divide\n",
-      "  angle = -np.sign(from_cent_2)*np.arccos(from_cent_1/np.sqrt(from_cent_1**2+from_cent_2**2))\n"
+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:174: RuntimeWarning: invalid value encountered in true_divide\n"
      ]
     }
    ],
    "source": [
-    "et_map, ex_map, radius_map, angle_map = getTangetial(e1_map, e2_map, [center_1, center_2], dx=dx.value)"
+    "et_map, ex_map, radius_map, angle_map = u.getTangetial(e1_map, e2_map, [center_1, center_2], dx=dx.value)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 15,
    "id": "e743f1b8",
    "metadata": {},
    "outputs": [
@@ -3376,7 +3372,7 @@
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        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2022-10-06T15:35:30.448461</dc:date>\n",
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        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -3407,8 +3403,8 @@
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        "   </g>\n",
-       "   <g clip-path=\"url(#p6b62705667)\">\n",
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+       "   <g clip-path=\"url(#p32eb17a932)\">\n",
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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
@@ -3417,10 +3413,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"mb9111e2595\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"m2aab82d911\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#mb9111e2595\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#m2aab82d911\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -3456,7 +3452,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#mb9111e2595\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#m2aab82d911\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -3487,7 +3483,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"118.437344\" xlink:href=\"#mb9111e2595\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"118.437344\" xlink:href=\"#m2aab82d911\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -3528,7 +3524,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#mb9111e2595\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#m2aab82d911\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -3577,7 +3573,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#mb9111e2595\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#m2aab82d911\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -3613,7 +3609,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"245.843594\" xlink:href=\"#mb9111e2595\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"245.843594\" xlink:href=\"#m2aab82d911\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -3659,10 +3655,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L -3.5 0 \n",
-       "\" id=\"me61fa2c4ba\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"m61c97259bf\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#me61fa2c4ba\" y=\"10.999219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m61c97259bf\" y=\"10.999219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -3675,7 +3671,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#me61fa2c4ba\" y=\"53.467969\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m61c97259bf\" y=\"53.467969\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -3690,7 +3686,7 @@
        "    <g id=\"ytick_3\">\n",
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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
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        "      </defs>\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#m6e548b85aa\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -4080,7 +4076,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#m6e548b85aa\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
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@@ -4111,7 +4107,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"118.437344\" xlink:href=\"#m6e548b85aa\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -4152,7 +4148,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#m6e548b85aa\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -4201,7 +4197,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#m49a30493ee\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#m6e548b85aa\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -4237,7 +4233,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"245.843594\" xlink:href=\"#m49a30493ee\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"245.843594\" xlink:href=\"#m6e548b85aa\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -4283,10 +4279,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L -3.5 0 \n",
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+       "\" id=\"m9bb5998d0f\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#mb903a26884\" y=\"10.999219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m9bb5998d0f\" y=\"10.999219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -4299,7 +4295,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m9bb5998d0f\" y=\"53.467969\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -4314,7 +4310,7 @@
        "    <g id=\"ytick_3\">\n",
        "     <g id=\"line2d_9\">\n",
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   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 16,
    "id": "e3d066a0",
    "metadata": {},
    "outputs": [
@@ -4642,15 +4638,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/cdavies/CLMM_testing/modelling.py:190: RuntimeWarning: invalid value encountered in true_divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/home/cdavies/CLMM_testing/modelling.py:191: RuntimeWarning: invalid value encountered in true_divide\n",
-      "  gammat_radial = _GT/_N\n"
+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:200: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:201: RuntimeWarning: invalid value encountered in true_divide\n"
      ]
     }
    ],
    "source": [
-    "kappa_radial, gammat_radial = getRadial(radius_map,r_bins,\n",
+    "kappa_radial, gammat_radial = u.getRadial(radius_map,r_bins,\n",
     "                                        angle_map,phi_bins,kappa_map,et_map)"
    ]
   },
@@ -4664,7 +4658,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 17,
    "id": "080ff2f4",
    "metadata": {},
    "outputs": [
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#mda4d5824dd\" y=\"155.959219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_10\">\n",
@@ -4958,7 +4952,7 @@
        "    <g id=\"ytick_6\">\n",
        "     <g id=\"line2d_11\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#m88ecd59b43\" y=\"192.199219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#mda4d5824dd\" y=\"192.199219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_11\">\n",
@@ -4993,7 +4987,7 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
-       "  <clipPath id=\"p766798092e\">\n",
+       "  <clipPath id=\"p6a5d2498f5\">\n",
        "   <rect height=\"217.44\" width=\"181.2\" x=\"26.925\" y=\"7.375219\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
@@ -5019,7 +5013,7 @@
        "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2022-10-06T15:35:52.273201</dc:date>\n",
+       "    <dc:date>2022-11-09T16:07:00.279754</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -5050,8 +5044,8 @@
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p80fb7864e0)\">\n",
-       "    <image height=\"218\" id=\"imagea6ecb2f818\" transform=\"scale(1 -1)translate(0 -218)\" width=\"182\" x=\"26.925\" xlink:href=\"data:image/png;base64,\n",
+       "   <g clip-path=\"url(#p0e600d449a)\">\n",
+       "    <image height=\"218\" id=\"image9d909a8d8d\" transform=\"scale(1 -1)translate(0 -218)\" width=\"182\" x=\"26.925\" xlink:href=\"data:image/png;base64,\n",
        "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\" y=\"-6.815219\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
@@ -5060,10 +5054,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"mb11324c650\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"ma1e3dfc76b\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"30.549\" xlink:href=\"#mb11324c650\" y=\"224.815219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"30.549\" xlink:href=\"#ma1e3dfc76b\" y=\"224.815219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -5099,7 +5093,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"66.789\" xlink:href=\"#mb11324c650\" y=\"224.815219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"66.789\" xlink:href=\"#ma1e3dfc76b\" y=\"224.815219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -5139,7 +5133,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"103.029\" xlink:href=\"#mb11324c650\" y=\"224.815219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"103.029\" xlink:href=\"#ma1e3dfc76b\" y=\"224.815219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -5169,7 +5163,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"139.269\" xlink:href=\"#mb11324c650\" y=\"224.815219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"139.269\" xlink:href=\"#ma1e3dfc76b\" y=\"224.815219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -5183,7 +5177,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"175.509\" xlink:href=\"#mb11324c650\" y=\"224.815219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"175.509\" xlink:href=\"#ma1e3dfc76b\" y=\"224.815219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -5227,10 +5221,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L -3.5 0 \n",
-       "\" id=\"ma20b142cae\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"mb7e9f1e8c2\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#ma20b142cae\" y=\"10.999219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#mb7e9f1e8c2\" y=\"10.999219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -5243,7 +5237,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_7\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#ma20b142cae\" y=\"47.239219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#mb7e9f1e8c2\" y=\"47.239219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -5256,7 +5250,7 @@
        "    <g id=\"ytick_3\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#ma20b142cae\" y=\"83.479219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#mb7e9f1e8c2\" y=\"83.479219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -5270,7 +5264,7 @@
        "    <g id=\"ytick_4\">\n",
        "     <g id=\"line2d_9\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#ma20b142cae\" y=\"119.719219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#mb7e9f1e8c2\" y=\"119.719219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_9\">\n",
@@ -5284,7 +5278,7 @@
        "    <g id=\"ytick_5\">\n",
        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#ma20b142cae\" y=\"155.959219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#mb7e9f1e8c2\" y=\"155.959219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_10\">\n",
@@ -5298,7 +5292,7 @@
        "    <g id=\"ytick_6\">\n",
        "     <g id=\"line2d_11\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#ma20b142cae\" y=\"192.199219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#mb7e9f1e8c2\" y=\"192.199219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_11\">\n",
@@ -5333,7 +5327,7 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
-       "  <clipPath id=\"p80fb7864e0\">\n",
+       "  <clipPath id=\"p0e600d449a\">\n",
        "   <rect height=\"217.44\" width=\"181.2\" x=\"26.925\" y=\"7.375219\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
@@ -5367,7 +5361,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 18,
    "id": "5c6174be",
    "metadata": {},
    "outputs": [],
@@ -5386,7 +5380,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 19,
    "id": "29a26710",
    "metadata": {},
    "outputs": [
@@ -5401,7 +5395,7 @@
        "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2022-10-06T15:35:52.431149</dc:date>\n",
+       "    <dc:date>2022-11-09T16:07:06.672827</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -5438,10 +5432,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"m12f79f0150\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"mad8a61676f\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"53.59923\" xlink:href=\"#m12f79f0150\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"53.59923\" xlink:href=\"#mad8a61676f\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -5477,7 +5471,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"109.392075\" xlink:href=\"#m12f79f0150\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"109.392075\" xlink:href=\"#mad8a61676f\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -5506,7 +5500,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"165.18492\" xlink:href=\"#m12f79f0150\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"165.18492\" xlink:href=\"#mad8a61676f\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -5545,7 +5539,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"220.977765\" xlink:href=\"#m12f79f0150\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"220.977765\" xlink:href=\"#mad8a61676f\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -5592,7 +5586,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"276.77061\" xlink:href=\"#m12f79f0150\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"276.77061\" xlink:href=\"#mad8a61676f\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -5626,7 +5620,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"332.563455\" xlink:href=\"#m12f79f0150\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"332.563455\" xlink:href=\"#mad8a61676f\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -5787,10 +5781,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L -3.5 0 \n",
-       "\" id=\"ma32e29dd26\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"meebc6a2b42\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"43.78125\" xlink:href=\"#ma32e29dd26\" y=\"218.834548\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"43.78125\" xlink:href=\"#meebc6a2b42\" y=\"218.834548\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -5814,7 +5808,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"43.78125\" xlink:href=\"#ma32e29dd26\" y=\"188.538556\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"43.78125\" xlink:href=\"#meebc6a2b42\" y=\"188.538556\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_9\">\n",
@@ -5829,7 +5823,7 @@
        "    <g id=\"ytick_3\">\n",
        "     <g id=\"line2d_9\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"43.78125\" xlink:href=\"#ma32e29dd26\" y=\"158.242564\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"43.78125\" xlink:href=\"#meebc6a2b42\" y=\"158.242564\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_10\">\n",
@@ -5844,7 +5838,7 @@
        "    <g id=\"ytick_4\">\n",
        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
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        "      </g>\n",
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@@ -5859,7 +5853,7 @@
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@@ -5874,7 +5868,7 @@
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@@ -5889,7 +5883,7 @@
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@@ -6229,7 +6223,7 @@
        "    </g>\n",
        "   </g>\n",
        "   <g id=\"line2d_14\">\n",
-       "    <path clip-path=\"url(#p1ccafbc58c)\" d=\"M 58.999432 17.083636 \n",
+       "    <path clip-path=\"url(#p02895efab8)\" d=\"M 58.999432 17.083636 \n",
        "L 60.451876 19.231629 \n",
        "L 62.29497 21.469066 \n",
        "L 64.633785 23.929685 \n",
@@ -6250,7 +6244,7 @@
        "\" style=\"fill:none;stroke:#1f77b4;stroke-linecap:square;stroke-width:1.5;\"/>\n",
        "   </g>\n",
        "   <g id=\"line2d_15\">\n",
-       "    <path clip-path=\"url(#p1ccafbc58c)\" d=\"M 58.999432 212.476247 \n",
+       "    <path clip-path=\"url(#p02895efab8)\" d=\"M 58.999432 212.476247 \n",
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        "L 62.29497 211.765488 \n",
        "L 64.633785 214.441991 \n",
@@ -6442,7 +6436,7 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
-       "  <clipPath id=\"p1ccafbc58c\">\n",
+       "  <clipPath id=\"p02895efab8\">\n",
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@@ -6478,7 +6472,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 21,
    "id": "13660944",
    "metadata": {},
    "outputs": [
@@ -6486,10 +6480,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/cdavies/CLMM_testing/modelling.py:190: RuntimeWarning: invalid value encountered in true_divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/home/cdavies/CLMM_testing/modelling.py:191: RuntimeWarning: invalid value encountered in true_divide\n",
-      "  gammat_radial = _GT/_N\n"
+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:200: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:201: RuntimeWarning: invalid value encountered in true_divide\n"
      ]
     }
    ],
@@ -6504,9 +6496,9 @@
     "center_1 = R_mis*np.cos(_phi_Rmis)\n",
     "center_2 = R_mis*np.sin(_phi_Rmis)\n",
     "\n",
-    "et_map, ex_map, radius_map, angle_map = getTangetial(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
+    "et_map, ex_map, radius_map, angle_map = u.getTangetial(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
     "\n",
-    "kappa_radial, gammat_radial = getRadial(radius_map,r_bins,\n",
+    "kappa_radial, gammat_radial = u.getRadial(radius_map,r_bins,\n",
     "                                              angle_map,phi_bins,kappa_map,et_map)"
    ]
   },
@@ -6520,7 +6512,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 23,
    "id": "32772d61",
    "metadata": {},
    "outputs": [
@@ -6535,7 +6527,7 @@
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        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2022-10-06T15:36:14.789394</dc:date>\n",
+       "    <dc:date>2022-11-09T16:07:37.643290</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -6566,8 +6558,8 @@
        "z\n",
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        "   </g>\n",
-       "   <g clip-path=\"url(#p45efcde97c)\">\n",
-       "    <image height=\"148\" id=\"imageffb340597f\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
+       "   <g clip-path=\"url(#pd0af9211ab)\">\n",
+       "    <image height=\"148\" id=\"image8e6d067c87\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
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+       "   <g clip-path=\"url(#p4ad6c2f3e1)\">\n",
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        "   </g>\n",
        "   <g id=\"matplotlib.axis_3\">\n",
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.678803\" xlink:href=\"#mf430b381ad\" y=\"170.024007\"/>\n",
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        "     <g id=\"text_11\">\n",
@@ -6936,7 +6928,7 @@
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        "     <g id=\"text_12\">\n",
@@ -6951,7 +6943,7 @@
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        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"326.074023\" xlink:href=\"#md5d0a03ed8\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"326.074023\" xlink:href=\"#mf430b381ad\" y=\"170.024007\"/>\n",
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        "     </g>\n",
        "     <g id=\"text_13\">\n",
@@ -6968,7 +6960,7 @@
        "    <g id=\"ytick_7\">\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5d9a19782f\" y=\"169.879763\"/>\n",
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        "     </g>\n",
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@@ -6981,7 +6973,7 @@
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5d9a19782f\" y=\"141.030958\"/>\n",
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        "     <g id=\"text_15\">\n",
@@ -6996,7 +6988,7 @@
        "    <g id=\"ytick_9\">\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5d9a19782f\" y=\"112.182153\"/>\n",
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@@ -7011,7 +7003,7 @@
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5d9a19782f\" y=\"83.333348\"/>\n",
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@@ -7026,7 +7018,7 @@
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        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5d9a19782f\" y=\"54.484543\"/>\n",
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@@ -7041,7 +7033,7 @@
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        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5d9a19782f\" y=\"25.635738\"/>\n",
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@@ -7125,15 +7117,15 @@
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        "   </g>\n",
-       "   <g clip-path=\"url(#p6ba871a7da)\">\n",
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\" y=\"-22.024007\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_5\">\n",
        "    <g id=\"xtick_7\">\n",
        "     <g id=\"line2d_19\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.925862\" xlink:href=\"#md5d0a03ed8\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.925862\" xlink:href=\"#mf430b381ad\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_21\">\n",
@@ -7146,7 +7138,7 @@
        "    <g id=\"xtick_8\">\n",
        "     <g id=\"line2d_20\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"445.623472\" xlink:href=\"#md5d0a03ed8\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"445.623472\" xlink:href=\"#mf430b381ad\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_22\">\n",
@@ -7161,7 +7153,7 @@
        "    <g id=\"xtick_9\">\n",
        "     <g id=\"line2d_21\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"503.321082\" xlink:href=\"#md5d0a03ed8\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"503.321082\" xlink:href=\"#mf430b381ad\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_23\">\n",
@@ -7178,7 +7170,7 @@
        "    <g id=\"ytick_13\">\n",
        "     <g id=\"line2d_22\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m3e0f7a7dc0\" y=\"169.879763\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5d9a19782f\" y=\"169.879763\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_24\">\n",
@@ -7191,7 +7183,7 @@
        "    <g id=\"ytick_14\">\n",
        "     <g id=\"line2d_23\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m3e0f7a7dc0\" y=\"141.030958\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5d9a19782f\" y=\"141.030958\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_25\">\n",
@@ -7206,7 +7198,7 @@
        "    <g id=\"ytick_15\">\n",
        "     <g id=\"line2d_24\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m3e0f7a7dc0\" y=\"112.182153\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5d9a19782f\" y=\"112.182153\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_26\">\n",
@@ -7221,7 +7213,7 @@
        "    <g id=\"ytick_16\">\n",
        "     <g id=\"line2d_25\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m3e0f7a7dc0\" y=\"83.333348\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5d9a19782f\" y=\"83.333348\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_27\">\n",
@@ -7236,7 +7228,7 @@
        "    <g id=\"ytick_17\">\n",
        "     <g id=\"line2d_26\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m3e0f7a7dc0\" y=\"54.484543\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5d9a19782f\" y=\"54.484543\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_28\">\n",
@@ -7251,7 +7243,7 @@
        "    <g id=\"ytick_18\">\n",
        "     <g id=\"line2d_27\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m3e0f7a7dc0\" y=\"25.635738\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5d9a19782f\" y=\"25.635738\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_29\">\n",
@@ -7301,15 +7293,15 @@
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p48cafde8fa)\">\n",
-       "    <image height=\"148\" id=\"imagea1b27a4c69\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
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\" y=\"-199.929462\"/>\n",
+       "   <g clip-path=\"url(#p3a535c0c75)\">\n",
+       "    <image height=\"148\" id=\"image982aa41887\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
+       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\" y=\"-199.929462\"/>\n",
+       "   <g clip-path=\"url(#pc0b86d15dc)\">\n",
+       "    <image height=\"148\" id=\"image63d2b65b50\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"210.534559\" xlink:href=\"data:image/png;base64,\n",
+       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        "    <g id=\"xtick_13\">\n",
        "     <g id=\"line2d_37\">\n",
        "      <g>\n",
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@@ -7525,7 +7517,7 @@
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@@ -7540,7 +7532,7 @@
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@@ -7557,7 +7549,7 @@
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@@ -7570,7 +7562,7 @@
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5d9a19782f\" y=\"318.936413\"/>\n",
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@@ -7585,7 +7577,7 @@
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-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m3e0f7a7dc0\" y=\"290.087608\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5d9a19782f\" y=\"290.087608\"/>\n",
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@@ -7600,7 +7592,7 @@
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5d9a19782f\" y=\"261.238802\"/>\n",
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@@ -7615,7 +7607,7 @@
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        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5d9a19782f\" y=\"232.389997\"/>\n",
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@@ -7630,7 +7622,7 @@
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5d9a19782f\" y=\"203.541192\"/>\n",
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@@ -7701,7 +7693,7 @@
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        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"390.617172\" xlink:href=\"#mf430b381ad\" y=\"348.203793\"/>\n",
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        "     </g>\n",
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@@ -7714,7 +7706,7 @@
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        "     <g id=\"line2d_47\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"453.770632\" xlink:href=\"#md5d0a03ed8\" y=\"348.203793\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"453.770632\" xlink:href=\"#mf430b381ad\" y=\"348.203793\"/>\n",
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        "      <g>\n",
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        "      <g>\n",
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        "      <g>\n",
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        "     </g>\n",
        "     <g id=\"text_8\">\n",
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        "     </g>\n",
        "     <g id=\"text_9\">\n",
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        "     <g id=\"line2d_9\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"40.603125\" xlink:href=\"#mf0962eb85f\" y=\"110.58358\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"40.603125\" xlink:href=\"#md69d22a350\" y=\"110.58358\"/>\n",
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        "     </g>\n",
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        "      <g>\n",
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        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"40.603125\" xlink:href=\"#md69d22a350\" y=\"49.710852\"/>\n",
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        "     <g id=\"text_12\">\n",
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@@ -8526,7 +8518,7 @@
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@@ -8553,7 +8545,7 @@
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@@ -8589,7 +8581,7 @@
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@@ -8748,10 +8740,10 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
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+       "  <clipPath id=\"pe9acb7de16\">\n",
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        "  </clipPath>\n",
-       "  <clipPath id=\"pb9ff740163\">\n",
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        " </defs>\n",
@@ -8768,7 +8760,7 @@
     }
    ],
    "source": [
-    "plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map,ex_map,\n",
+    "u.plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map,ex_map,\n",
     "                       kappa_radial,gammat_radial,r_bins)"
    ]
   },
@@ -8790,7 +8782,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 24,
    "id": "38b199f1",
    "metadata": {},
    "outputs": [],
@@ -8803,7 +8795,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 25,
    "id": "c17883c2",
    "metadata": {},
    "outputs": [
@@ -8811,12 +8803,9 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/cdavies/CLMM_testing/modelling.py:165: RuntimeWarning: invalid value encountered in true_divide\n",
-      "  angle = -np.sign(from_cent_2)*np.arccos(from_cent_1/np.sqrt(from_cent_1**2+from_cent_2**2))\n",
-      "/home/cdavies/CLMM_testing/modelling.py:190: RuntimeWarning: invalid value encountered in true_divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/home/cdavies/CLMM_testing/modelling.py:191: RuntimeWarning: invalid value encountered in true_divide\n",
-      "  gammat_radial = _GT/_N\n"
+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:174: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:200: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:201: RuntimeWarning: invalid value encountered in true_divide\n"
      ]
     }
    ],
@@ -8837,15 +8826,15 @@
     "    center_1 = R_mis_arr[j]*np.cos(_phi_Rmis)\n",
     "    center_2 = R_mis_arr[j]*np.sin(_phi_Rmis)\n",
     "\n",
-    "    et_map[j], ex_map[j], radius_map[j], angle_map[j] = getTangetial(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
+    "    et_map[j], ex_map[j], radius_map[j], angle_map[j] = u.getTangetial(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
     "\n",
-    "    kappa_radial[j], gammat_radial[j] = getRadial(radius_map[j],r_bins,\n",
+    "    kappa_radial[j], gammat_radial[j] = u.getRadial(radius_map[j],r_bins,\n",
     "                                                  angle_map[j],phi_bins,kappa_map,et_map[j])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 26,
    "id": "22ba0469",
    "metadata": {},
    "outputs": [
@@ -8860,7 +8849,7 @@
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        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2022-10-06T15:48:49.844858</dc:date>\n",
+       "    <dc:date>2022-11-09T16:11:39.719159</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -8891,8 +8880,8 @@
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p83c7f6a98f)\">\n",
-       "    <image height=\"148\" id=\"image92f55aca8f\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
+       "   <g clip-path=\"url(#p409b085521)\">\n",
+       "    <image height=\"148\" id=\"imagef919a30395\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
        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+       "   <g clip-path=\"url(#pb7d831a949)\">\n",
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y=\"-22.024007\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_3\">\n",
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.678803\" xlink:href=\"#m9124cecd13\" y=\"170.024007\"/>\n",
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        "     <g id=\"text_11\">\n",
@@ -9261,7 +9250,7 @@
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        "      <g>\n",
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        "     <g id=\"text_12\">\n",
@@ -9276,7 +9265,7 @@
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        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"326.074023\" xlink:href=\"#mf960789ac4\" y=\"170.024007\"/>\n",
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        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_13\">\n",
@@ -9293,7 +9282,7 @@
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        "      <g>\n",
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        "     <g id=\"text_14\">\n",
@@ -9306,7 +9295,7 @@
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m1b5f838c68\" y=\"141.030958\"/>\n",
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@@ -9321,7 +9310,7 @@
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@@ -9336,7 +9325,7 @@
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m1b5f838c68\" y=\"83.333348\"/>\n",
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@@ -9351,7 +9340,7 @@
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        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m1b5f838c68\" y=\"54.484543\"/>\n",
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@@ -9366,7 +9355,7 @@
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        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m1b5f838c68\" y=\"25.635738\"/>\n",
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        "     <g id=\"text_19\">\n",
@@ -9450,15 +9439,15 @@
        "z\n",
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        "   </g>\n",
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+       "   <g clip-path=\"url(#p7035afc62c)\">\n",
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\" y=\"-22.024007\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_5\">\n",
        "    <g id=\"xtick_7\">\n",
        "     <g id=\"line2d_19\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.925862\" xlink:href=\"#mf960789ac4\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.925862\" xlink:href=\"#m9124cecd13\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_21\">\n",
@@ -9471,7 +9460,7 @@
        "    <g id=\"xtick_8\">\n",
        "     <g id=\"line2d_20\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"445.623472\" xlink:href=\"#mf960789ac4\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"445.623472\" xlink:href=\"#m9124cecd13\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_22\">\n",
@@ -9486,7 +9475,7 @@
        "    <g id=\"xtick_9\">\n",
        "     <g id=\"line2d_21\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"503.321082\" xlink:href=\"#mf960789ac4\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"503.321082\" xlink:href=\"#m9124cecd13\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_23\">\n",
@@ -9503,7 +9492,7 @@
        "    <g id=\"ytick_13\">\n",
        "     <g id=\"line2d_22\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m9c85f503b7\" y=\"169.879763\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m1b5f838c68\" y=\"169.879763\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_24\">\n",
@@ -9516,7 +9505,7 @@
        "    <g id=\"ytick_14\">\n",
        "     <g id=\"line2d_23\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m9c85f503b7\" y=\"141.030958\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m1b5f838c68\" y=\"141.030958\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_25\">\n",
@@ -9531,7 +9520,7 @@
        "    <g id=\"ytick_15\">\n",
        "     <g id=\"line2d_24\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m9c85f503b7\" y=\"112.182153\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m1b5f838c68\" y=\"112.182153\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_26\">\n",
@@ -9546,7 +9535,7 @@
        "    <g id=\"ytick_16\">\n",
        "     <g id=\"line2d_25\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m9c85f503b7\" y=\"83.333348\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m1b5f838c68\" y=\"83.333348\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_27\">\n",
@@ -9561,7 +9550,7 @@
        "    <g id=\"ytick_17\">\n",
        "     <g id=\"line2d_26\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m9c85f503b7\" y=\"54.484543\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m1b5f838c68\" y=\"54.484543\"/>\n",
        "      </g>\n",
        "     </g>\n",
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@@ -9576,7 +9565,7 @@
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        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m9c85f503b7\" y=\"25.635738\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m1b5f838c68\" y=\"25.635738\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_29\">\n",
@@ -9626,15 +9615,15 @@
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#pd53c6ca1f5)\">\n",
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\" y=\"-199.929462\"/>\n",
+       "   <g clip-path=\"url(#p9dfafd6553)\">\n",
+       "    <image height=\"148\" id=\"imagea31cb6981f\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
+       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        "   </g>\n",
        "   <g id=\"matplotlib.axis_7\">\n",
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@@ -9829,15 +9818,15 @@
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\" y=\"-199.929462\"/>\n",
+       "   <g clip-path=\"url(#pba5a3b345b)\">\n",
+       "    <image height=\"148\" id=\"image27059af5ef\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"210.534559\" xlink:href=\"data:image/png;base64,\n",
+       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+       "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\" y=\"-21.936307\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_3\">\n",
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_12\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"226.264943\" xlink:href=\"#m2666b59db9\" y=\"204.936307\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"226.264943\" xlink:href=\"#m1502e261cf\" y=\"204.936307\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_15\">\n",
@@ -10808,7 +10797,7 @@
        "    <g id=\"xtick_7\">\n",
        "     <g id=\"line2d_13\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"256.701307\" xlink:href=\"#m2666b59db9\" y=\"204.936307\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"256.701307\" xlink:href=\"#m1502e261cf\" y=\"204.936307\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_16\">\n",
@@ -10821,7 +10810,7 @@
        "    <g id=\"xtick_8\">\n",
        "     <g id=\"line2d_14\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"287.13767\" xlink:href=\"#m2666b59db9\" y=\"204.936307\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"287.13767\" xlink:href=\"#m1502e261cf\" y=\"204.936307\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_17\">\n",
@@ -10835,7 +10824,7 @@
        "    <g id=\"xtick_9\">\n",
        "     <g id=\"line2d_15\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"317.574034\" xlink:href=\"#m2666b59db9\" y=\"204.936307\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"317.574034\" xlink:href=\"#m1502e261cf\" y=\"204.936307\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_18\">\n",
@@ -10849,7 +10838,7 @@
        "    <g id=\"xtick_10\">\n",
        "     <g id=\"line2d_16\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"348.010398\" xlink:href=\"#m2666b59db9\" y=\"204.936307\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"348.010398\" xlink:href=\"#m1502e261cf\" y=\"204.936307\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_19\">\n",
@@ -10871,7 +10860,7 @@
        "    <g id=\"ytick_7\">\n",
        "     <g id=\"line2d_17\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m480884496d\" y=\"201.89267\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#ma033c20fd0\" y=\"201.89267\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_21\">\n",
@@ -10884,7 +10873,7 @@
        "    <g id=\"ytick_8\">\n",
        "     <g id=\"line2d_18\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m480884496d\" y=\"171.456307\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#ma033c20fd0\" y=\"171.456307\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_22\">\n",
@@ -10897,7 +10886,7 @@
        "    <g id=\"ytick_9\">\n",
        "     <g id=\"line2d_19\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m480884496d\" y=\"141.019943\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#ma033c20fd0\" y=\"141.019943\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_23\">\n",
@@ -10911,7 +10900,7 @@
        "    <g id=\"ytick_10\">\n",
        "     <g id=\"line2d_20\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m480884496d\" y=\"110.58358\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#ma033c20fd0\" y=\"110.58358\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_24\">\n",
@@ -10925,7 +10914,7 @@
        "    <g id=\"ytick_11\">\n",
        "     <g id=\"line2d_21\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m480884496d\" y=\"80.147216\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#ma033c20fd0\" y=\"80.147216\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_25\">\n",
@@ -10939,7 +10928,7 @@
        "    <g id=\"ytick_12\">\n",
        "     <g id=\"line2d_22\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m480884496d\" y=\"49.710852\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#ma033c20fd0\" y=\"49.710852\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_26\">\n",
@@ -11030,10 +11019,10 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
-       "  <clipPath id=\"p65e18af12f\">\n",
+       "  <clipPath id=\"pb37736bdcd\">\n",
        "   <rect height=\"182.618182\" width=\"152.181818\" x=\"40.603125\" y=\"22.318125\"/>\n",
        "  </clipPath>\n",
-       "  <clipPath id=\"p0698251f1d\">\n",
+       "  <clipPath id=\"p437b873549\">\n",
        "   <rect height=\"182.618182\" width=\"152.181818\" x=\"223.221307\" y=\"22.318125\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
@@ -11051,7 +11040,7 @@
    ],
    "source": [
     "R_mis_ind = 10\n",
-    "plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map[R_mis_ind],ex_map[R_mis_ind],\n",
+    "u.plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map[R_mis_ind],ex_map[R_mis_ind],\n",
     "                       kappa_radial[R_mis_ind],gammat_radial[R_mis_ind],r_bins)"
    ]
   },
@@ -11065,7 +11054,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 27,
    "id": "7e458c10",
    "metadata": {},
    "outputs": [
@@ -11080,7 +11069,7 @@
        "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2022-10-06T15:54:06.893343</dc:date>\n",
+       "    <dc:date>2022-11-09T16:11:40.345236</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -11117,15 +11106,15 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"m8f77dc2246\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"me6a171ce56\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"47.444141\" xlink:href=\"#m8f77dc2246\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"46.283605\" xlink:href=\"#me6a171ce56\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
        "      <!-- 0 -->\n",
-       "      <g transform=\"translate(44.262891 239.238438)scale(0.1 -0.1)\">\n",
+       "      <g transform=\"translate(43.102355 239.238437)scale(0.1 -0.1)\">\n",
        "       <defs>\n",
        "        <path d=\"M 2034 4250 \n",
        "Q 1547 4250 1301 3770 \n",
@@ -11156,12 +11145,12 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"103.027957\" xlink:href=\"#m8f77dc2246\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"102.07645\" xlink:href=\"#me6a171ce56\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
        "      <!-- 1 -->\n",
-       "      <g transform=\"translate(99.846707 239.238438)scale(0.1 -0.1)\">\n",
+       "      <g transform=\"translate(98.8952 239.238437)scale(0.1 -0.1)\">\n",
        "       <defs>\n",
        "        <path d=\"M 794 531 \n",
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@@ -11185,12 +11174,12 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"158.611773\" xlink:href=\"#m8f77dc2246\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"157.869295\" xlink:href=\"#me6a171ce56\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
        "      <!-- 2 -->\n",
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+       "      <g transform=\"translate(154.688045 239.238437)scale(0.1 -0.1)\">\n",
        "       <defs>\n",
        "        <path d=\"M 1228 531 \n",
        "L 3431 531 \n",
@@ -11224,12 +11213,12 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"214.19559\" xlink:href=\"#m8f77dc2246\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"213.66214\" xlink:href=\"#me6a171ce56\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
        "      <!-- 3 -->\n",
-       "      <g transform=\"translate(211.01434 239.238438)scale(0.1 -0.1)\">\n",
+       "      <g transform=\"translate(210.48089 239.238437)scale(0.1 -0.1)\">\n",
        "       <defs>\n",
        "        <path d=\"M 2597 2516 \n",
        "Q 3050 2419 3304 2112 \n",
@@ -11271,12 +11260,12 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"269.779406\" xlink:href=\"#m8f77dc2246\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"269.454985\" xlink:href=\"#me6a171ce56\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
        "      <!-- 4 -->\n",
-       "      <g transform=\"translate(266.598156 239.238438)scale(0.1 -0.1)\">\n",
+       "      <g transform=\"translate(266.273735 239.238437)scale(0.1 -0.1)\">\n",
        "       <defs>\n",
        "        <path d=\"M 2419 4116 \n",
        "L 825 1625 \n",
@@ -11305,12 +11294,12 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"325.363222\" xlink:href=\"#m8f77dc2246\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"325.24783\" xlink:href=\"#me6a171ce56\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
        "      <!-- 5 -->\n",
-       "      <g transform=\"translate(322.181972 239.238438)scale(0.1 -0.1)\">\n",
+       "      <g transform=\"translate(322.06658 239.238437)scale(0.1 -0.1)\">\n",
        "       <defs>\n",
        "        <path d=\"M 691 4666 \n",
        "L 3169 4666 \n",
@@ -11349,15 +11338,15 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L -3.5 0 \n",
-       "\" id=\"m2d3ede7996\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"mff676c5544\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"36.465625\" xlink:href=\"#m2d3ede7996\" y=\"212.69214\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"36.465625\" xlink:href=\"#mff676c5544\" y=\"212.703513\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
        "      <!-- 0.54 -->\n",
-       "      <g transform=\"translate(7.2 216.491359)scale(0.1 -0.1)\">\n",
+       "      <g transform=\"translate(7.2 216.502732)scale(0.1 -0.1)\">\n",
        "       <defs>\n",
        "        <path d=\"M 684 794 \n",
        "L 1344 794 \n",
@@ -11377,12 +11366,12 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"36.465625\" xlink:href=\"#m2d3ede7996\" y=\"181.780277\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"36.465625\" xlink:href=\"#mff676c5544\" y=\"181.817121\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
        "      <!-- 0.56 -->\n",
-       "      <g transform=\"translate(7.2 185.579496)scale(0.1 -0.1)\">\n",
+       "      <g transform=\"translate(7.2 185.616339)scale(0.1 -0.1)\">\n",
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@@ -12608,7 +12625,7 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
-       "  <clipPath id=\"p3c3a3f44e7\">\n",
+       "  <clipPath id=\"p6aee157f7e\">\n",
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From d9a7cd435707459cf9a0aaa439a2bff5f67c4744 Mon Sep 17 00:00:00 2001
From: Chris Davies <cdavies@cosmogw.kosmo.physik.uni-muenchen.de>
Date: Thu, 10 Nov 2022 14:27:55 +0100
Subject: [PATCH 05/14] updated functions to use clmm constants rather than
 astropy constants

---
 clmm/utils.py | 63 +++++++--------------------------------------------
 1 file changed, 8 insertions(+), 55 deletions(-)

diff --git a/clmm/utils.py b/clmm/utils.py
index a9e774fe1..da0579d69 100644
--- a/clmm/utils.py
+++ b/clmm/utils.py
@@ -10,7 +10,6 @@
 import matplotlib.pyplot as plt
 
 from astropy.cosmology import LambdaCDM #update
-from astropy import constants as astconst #update
 
 class profiles:
     '''A class to generate 2D covnergence profiles on a regular grid
@@ -80,15 +79,20 @@ def kappa_NFW(self,r_vals=None):
         if np.all(r_vals.value) == None:
             r_vals = self.r_vals
         
+        G = const.GNEWT.value * u.N * u.m**2 /u.kg**2
+        c = const.CLIGHT.value * u.m / u.s
+        Msol = const.SOLAR_MASS.value * u.kg 
+
         cosmo = LambdaCDM(H0=self.H_0, Om0=self.Omega_m, Ode0=self.Omega_Lambda, Tcmb0=self.Tcmb0)
 
-        r_200 = ( (astconst.G * self.M)/(100. * cosmo.H(self.z_l)**2) )**(1./3.)
+        r_200 = ( (G * self.M)/(100. * cosmo.H(self.z_l)**2) )**(1./3.)
         r_s = r_200 * self.c
         delta_c = (200./3.) * ( self.c**3 / ( np.log(1+self.c) - ( self.c/(1+self.c) ) ) )
         
         x = r_vals/r_s
+        x = x.value
 
-        Sigma_crit_coeff = astconst.c**2 / (4. * np.pi * astconst.G)
+        Sigma_crit_coeff = c**2 / (4. * np.pi * G)
 
         D_s = cosmo.angular_diameter_distance(self.z_s)  
         D_d = cosmo.angular_diameter_distance(self.z_l)  
@@ -105,7 +109,7 @@ def kappa_NFW(self,r_vals=None):
         nfw = coeff * f_internal
 
         if self.sig:
-            return nfw.to(astconst.M_sun / u.Mpc**2).real
+            return nfw.to(Msol / u.Mpc**2).real
         if not self.sig:
             return (nfw.real / Sigma_crit).decompose()
 
@@ -203,57 +207,6 @@ def getRadial(radius_map,r_bins,angle_map,phi_bins,kappa_map,et_map):
     return kappa_radial,gammat_radial
 
 
-def plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map,ex_map,
-                       kappa_radial,gammat_radial,r_bins):
-    '''quickly plot the convergence, e1,e2, ex,et and radial profiles
-    '''
-    fig, ax = plt.subplots(2,3,figsize=[9,6])
-    ax.ravel()
-    
-    ax[0,0].imshow(kappa_map,origin = 'lower')
-    ax[0,0].set_title(r'$\kappa$')
-
-
-    ax[0,1].imshow(e1_map,origin = 'lower')
-    ax[0,1].set_title(r'$e_1$')
-
-
-    ax[0,2].imshow(e2_map,origin = 'lower')
-    ax[0,2].set_title(r'$e_2$')
-
-
-    ax[1,0].imshow(et_map,origin = 'lower')
-    ax[1,0].set_title(r'$e_t$')
-
-
-    ax[1,1].imshow(ex_map,origin = 'lower')
-    ax[1,1].set_title(r'$e_x$')
-
-    
-    
-    r_bins_mid = 0.5 * (r_bins[1:] + r_bins[:-1])
-
-    ax[1,2].plot(r_bins_mid, kappa_radial.mean(axis=-1), label=r'$\kappa(r)$')
-    ax[1,2].plot(r_bins_mid, gammat_radial.mean(axis=-1), label=r'$\gamma_t(r)$')
-    
-    plt.legend()
-    plt.show()
-    
-    fig,ax = plt.subplots(1,2)
-    
-    ax[0].imshow(kappa_radial,origin='lower')
-    ax[1].imshow(gammat_radial,origin='lower')
-    
-    ax[0].set_ylabel('r')
-    ax[0].set_xlabel('$\phi$')
-    
-    ax[1].set_ylabel('r')
-    ax[1].set_xlabel('$\phi$')
-    
-    ax[0].set_title(r'$\kappa$')
-    ax[1].set_title(r'$\gamma_t$')
-
-    plt.show()
 
 def compute_nfw_boost(rvals, rs=1000, b0=0.1) :
     """ Given a list of rvals, and optional rs and b0, return the corresponding boost factor at each rval

From ef26cbd0a2c41607c8eae5fcad15c4eace4b4afe Mon Sep 17 00:00:00 2001
From: Chris Davies <cdavies@cosmogw.kosmo.physik.uni-muenchen.de>
Date: Thu, 10 Nov 2022 14:29:31 +0100
Subject: [PATCH 06/14] moved plotting function from utils to demo_modelling
 since it is not a general function

---
 examples/demo_modelling.ipynb | 3419 ++++++++++++++++++---------------
 1 file changed, 1880 insertions(+), 1539 deletions(-)

diff --git a/examples/demo_modelling.ipynb b/examples/demo_modelling.ipynb
index 19bdc323e..cf4b70c94 100644
--- a/examples/demo_modelling.ipynb
+++ b/examples/demo_modelling.ipynb
@@ -13,7 +13,6 @@
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
     "import sys\n",
-    "#sys.path.append('/home/cdavies/CLMM/')\n",
     "import clmm\n",
     "from clmm import Cosmology\n",
     "from clmm.support import mock_data as mock\n",
@@ -118,15 +117,7 @@
    "execution_count": 5,
    "id": "5b51bbc8",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "WARNING: function 'sqrt' is not known to astropy's Quantity. Will run it anyway, hoping it will treat ndarray subclasses correctly. Please raise an issue at https://github.com/astropy/astropy/issues.  [astropy.units.quantity]\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "#lensing_map has the option to return either Sigma map or the convergence map.\n",
     "lensing_map = u.profiles(Mass, c, z_l, z_s, sig=False) \n",
@@ -151,7 +142,7 @@
        "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2022-11-09T16:03:52.275177</dc:date>\n",
+       "    <dc:date>2022-11-10T14:23:26.732168</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -182,8 +173,8 @@
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p35afa4834e)\">\n",
-       "    <image height=\"218\" id=\"image00e9359b3f\" transform=\"scale(1 -1)translate(0 -218)\" width=\"218\" x=\"48.982812\" xlink:href=\"data:image/png;base64,\n",
+       "   <g clip-path=\"url(#peee7dd125c)\">\n",
+       "    <image height=\"218\" id=\"imaged815d3a7c1\" transform=\"scale(1 -1)translate(0 -218)\" width=\"218\" x=\"48.982812\" xlink:href=\"data:image/png;base64,\n",
        "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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
@@ -192,10 +183,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"mc249ef2241\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"mf266ea4cda\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"48.982812\" xlink:href=\"#mc249ef2241\" y=\"228.439219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"48.982812\" xlink:href=\"#mf266ea4cda\" y=\"228.439219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -264,7 +255,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"103.342812\" xlink:href=\"#mc249ef2241\" y=\"228.439219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"103.342812\" xlink:href=\"#mf266ea4cda\" y=\"228.439219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -295,7 +286,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"157.702812\" xlink:href=\"#mc249ef2241\" y=\"228.439219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"157.702812\" xlink:href=\"#mf266ea4cda\" y=\"228.439219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -308,7 +299,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"212.062813\" xlink:href=\"#mc249ef2241\" y=\"228.439219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"212.062813\" xlink:href=\"#mf266ea4cda\" y=\"228.439219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -322,7 +313,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"266.422812\" xlink:href=\"#mc249ef2241\" y=\"228.439219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"266.422812\" xlink:href=\"#mf266ea4cda\" y=\"228.439219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -473,10 +464,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L -3.5 0 \n",
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+       "\" id=\"m505508a37d\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"48.982812\" xlink:href=\"#m27e0fa2ff4\" y=\"228.439219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"48.982812\" xlink:href=\"#m505508a37d\" y=\"228.439219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -491,7 +482,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_7\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"48.982812\" xlink:href=\"#m505508a37d\" y=\"201.259219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -533,7 +524,7 @@
        "    <g id=\"ytick_3\">\n",
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        "      <g>\n",
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@@ -690,7 +681,7 @@
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        "   <g id=\"patch_8\">\n",
-       "    <path clip-path=\"url(#pde8e3562be)\" d=\"M 283.162813 228.439219 \n",
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@@ -702,7 +693,7 @@
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        "   </g>\n",
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+       "   <image height=\"217\" id=\"imaged343d9ca39\" transform=\"scale(1 -1)translate(0 -217)\" width=\"11\" x=\"283\" xlink:href=\"data:image/png;base64,\n",
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@@ -728,25 +719,6 @@
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@@ -766,15 +738,15 @@
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        "    </g>\n",
-       "    <g id=\"ytick_12\">\n",
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-       "     <g id=\"text_19\">\n",
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@@ -815,15 +787,15 @@
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        "    </g>\n",
-       "    <g id=\"ytick_13\">\n",
-       "     <g id=\"line2d_18\">\n",
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        "     </g>\n",
-       "     <g id=\"text_20\">\n",
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@@ -832,15 +804,15 @@
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        "    </g>\n",
-       "    <g id=\"ytick_14\">\n",
-       "     <g id=\"line2d_19\">\n",
+       "    <g id=\"ytick_13\">\n",
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        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"294.034812\" xlink:href=\"#m243b2963f1\" y=\"96.369813\"/>\n",
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        "     </g>\n",
-       "     <g id=\"text_21\">\n",
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@@ -849,15 +821,15 @@
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        "    </g>\n",
-       "    <g id=\"ytick_15\">\n",
-       "     <g id=\"line2d_20\">\n",
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        "     </g>\n",
-       "     <g id=\"text_22\">\n",
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@@ -866,15 +838,15 @@
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        "    </g>\n",
-       "    <g id=\"ytick_16\">\n",
-       "     <g id=\"line2d_21\">\n",
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-       "     <g id=\"text_23\">\n",
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@@ -883,15 +855,15 @@
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        "    </g>\n",
-       "    <g id=\"ytick_17\">\n",
-       "     <g id=\"line2d_22\">\n",
+       "    <g id=\"ytick_16\">\n",
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        "     </g>\n",
-       "     <g id=\"text_24\">\n",
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@@ -900,6 +872,23 @@
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        "    </g>\n",
+       "    <g id=\"ytick_17\">\n",
+       "     <g id=\"line2d_22\">\n",
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+       "     <g id=\"text_24\">\n",
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@@ -940,10 +929,10 @@
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        " <defs>\n",
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@@ -978,7 +967,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "id": "2aaf9cb0",
    "metadata": {},
    "outputs": [],
@@ -991,7 +980,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "id": "72993065",
    "metadata": {},
    "outputs": [
@@ -1006,7 +995,7 @@
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        "   <cc:Work>\n",
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-       "    <dc:date>2022-11-09T16:06:03.757461</dc:date>\n",
+       "    <dc:date>2022-11-10T14:23:27.062237</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -1037,8 +1026,8 @@
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        "   </g>\n",
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+       "   <g clip-path=\"url(#p49e3b0aac0)\">\n",
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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
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        "      </defs>\n",
        "      <g>\n",
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        "      <g>\n",
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        "    <g id=\"xtick_4\">\n",
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        "      <g>\n",
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+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:150: RuntimeWarning: invalid value encountered in multiply\n"
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\" y=\"-10.226875\"/>\n",
+       "   <g clip-path=\"url(#p1dc9a0c05f)\">\n",
+       "    <image height=\"218\" id=\"image2cf395b2b0\" transform=\"scale(1 -1)translate(0 -218)\" width=\"218\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
+       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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
@@ -2065,10 +2052,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"m7fb05967c7\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"mf974cb2325\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#m7fb05967c7\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#mf974cb2325\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -2104,7 +2091,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#m7fb05967c7\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#mf974cb2325\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -2135,7 +2122,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"118.437344\" xlink:href=\"#m7fb05967c7\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"118.437344\" xlink:href=\"#mf974cb2325\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -2176,7 +2163,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#m7fb05967c7\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#mf974cb2325\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -2225,7 +2212,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#m7fb05967c7\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#mf974cb2325\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -2261,7 +2248,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"245.843594\" xlink:href=\"#m7fb05967c7\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"245.843594\" xlink:href=\"#mf974cb2325\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -2307,10 +2294,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L -3.5 0 \n",
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+       "\" id=\"m30d378b164\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#mdd2077d222\" y=\"10.999219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m30d378b164\" y=\"10.999219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -2323,7 +2310,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#mdd2077d222\" y=\"53.467969\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m30d378b164\" y=\"53.467969\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -2338,7 +2325,7 @@
        "    <g id=\"ytick_3\">\n",
        "     <g id=\"line2d_9\">\n",
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\" y=\"-10.226875\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
@@ -2736,10 +2755,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"md0b8068baf\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"mb72df415e3\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#md0b8068baf\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#mb72df415e3\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -2775,7 +2794,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#md0b8068baf\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#mb72df415e3\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -2806,7 +2825,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"118.437344\" xlink:href=\"#md0b8068baf\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"118.437344\" xlink:href=\"#mb72df415e3\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -2847,7 +2866,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#md0b8068baf\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#mb72df415e3\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -2896,7 +2915,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#md0b8068baf\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#mb72df415e3\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -2932,7 +2951,7 @@
        "    <g id=\"xtick_6\">\n",
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-       "    <dc:date>2022-11-09T16:06:29.108396</dc:date>\n",
+       "    <dc:date>2022-11-10T14:23:28.046848</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -3403,9 +3507,9 @@
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p32eb17a932)\">\n",
-       "    <image height=\"218\" id=\"image05e1af6a50\" transform=\"scale(1 -1)translate(0 -218)\" width=\"218\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
-       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\" y=\"-10.226875\"/>\n",
+       "   <g clip-path=\"url(#pa74a4beeb6)\">\n",
+       "    <image height=\"218\" id=\"imageddf74888f3\" transform=\"scale(1 -1)translate(0 -218)\" width=\"218\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
+       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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
@@ -3413,10 +3517,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"m2aab82d911\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"mf5297eb053\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#m2aab82d911\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#mf5297eb053\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -3452,7 +3556,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#m2aab82d911\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#mf5297eb053\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -3483,7 +3587,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"118.437344\" xlink:href=\"#m2aab82d911\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"118.437344\" xlink:href=\"#mf5297eb053\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -3524,7 +3628,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#m2aab82d911\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#mf5297eb053\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -3573,7 +3677,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#m2aab82d911\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#mf5297eb053\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -3609,7 +3713,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"245.843594\" xlink:href=\"#m2aab82d911\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"245.843594\" xlink:href=\"#mf5297eb053\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -3655,10 +3759,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L -3.5 0 \n",
-       "\" id=\"m61c97259bf\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"m9cd6245da0\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m61c97259bf\" y=\"10.999219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m9cd6245da0\" y=\"10.999219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -3671,7 +3775,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m61c97259bf\" y=\"53.467969\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m9cd6245da0\" y=\"53.467969\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -3686,7 +3790,7 @@
        "    <g id=\"ytick_3\">\n",
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\" y=\"-10.226875\"/>\n",
+       "   <g clip-path=\"url(#p003310dfb0)\">\n",
+       "    <image height=\"218\" id=\"image58a9675ed4\" transform=\"scale(1 -1)translate(0 -218)\" width=\"218\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
+       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y=\"-10.226875\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
@@ -4037,10 +4213,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"m6e548b85aa\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"m3628116860\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#m6e548b85aa\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#m3628116860\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -4076,7 +4252,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#m6e548b85aa\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#m3628116860\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -4107,7 +4283,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"118.437344\" xlink:href=\"#m6e548b85aa\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"118.437344\" xlink:href=\"#m3628116860\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -4148,7 +4324,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#m6e548b85aa\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#m3628116860\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -4197,7 +4373,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#m6e548b85aa\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#m3628116860\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -4233,7 +4409,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"245.843594\" xlink:href=\"#m6e548b85aa\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"245.843594\" xlink:href=\"#m3628116860\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -4279,10 +4455,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L -3.5 0 \n",
-       "\" id=\"m9bb5998d0f\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"m28de52a5a7\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m9bb5998d0f\" y=\"10.999219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m28de52a5a7\" y=\"10.999219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -4295,7 +4471,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m9bb5998d0f\" y=\"53.467969\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m28de52a5a7\" y=\"53.467969\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -4310,7 +4486,7 @@
        "    <g id=\"ytick_3\">\n",
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        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
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+       "   <g clip-path=\"url(#pea87f4251c)\">\n",
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+       "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\" y=\"-6.815219\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
@@ -5054,10 +5302,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"ma1e3dfc76b\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"m5d568179b9\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"30.549\" xlink:href=\"#ma1e3dfc76b\" y=\"224.815219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"30.549\" xlink:href=\"#m5d568179b9\" y=\"224.815219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -5093,7 +5341,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"66.789\" xlink:href=\"#ma1e3dfc76b\" y=\"224.815219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"66.789\" xlink:href=\"#m5d568179b9\" y=\"224.815219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -5133,7 +5381,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"103.029\" xlink:href=\"#ma1e3dfc76b\" y=\"224.815219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"103.029\" xlink:href=\"#m5d568179b9\" y=\"224.815219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -5163,7 +5411,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"139.269\" xlink:href=\"#ma1e3dfc76b\" y=\"224.815219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"139.269\" xlink:href=\"#m5d568179b9\" y=\"224.815219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -5177,7 +5425,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"175.509\" xlink:href=\"#ma1e3dfc76b\" y=\"224.815219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"175.509\" xlink:href=\"#m5d568179b9\" y=\"224.815219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -5221,10 +5469,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L -3.5 0 \n",
-       "\" id=\"mb7e9f1e8c2\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"md378364b3d\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#mb7e9f1e8c2\" y=\"10.999219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#md378364b3d\" y=\"10.999219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -5237,7 +5485,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_7\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#mb7e9f1e8c2\" y=\"47.239219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#md378364b3d\" y=\"47.239219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -5250,7 +5498,7 @@
        "    <g id=\"ytick_3\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#mb7e9f1e8c2\" y=\"83.479219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#md378364b3d\" y=\"83.479219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -5264,7 +5512,7 @@
        "    <g id=\"ytick_4\">\n",
        "     <g id=\"line2d_9\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#mb7e9f1e8c2\" y=\"119.719219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#md378364b3d\" y=\"119.719219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_9\">\n",
@@ -5278,7 +5526,7 @@
        "    <g id=\"ytick_5\">\n",
        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#mb7e9f1e8c2\" y=\"155.959219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#md378364b3d\" y=\"155.959219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_10\">\n",
@@ -5292,7 +5540,7 @@
        "    <g id=\"ytick_6\">\n",
        "     <g id=\"line2d_11\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#mb7e9f1e8c2\" y=\"192.199219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#md378364b3d\" y=\"192.199219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_11\">\n",
@@ -5327,7 +5575,7 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
-       "  <clipPath id=\"p0e600d449a\">\n",
+       "  <clipPath id=\"pea87f4251c\">\n",
        "   <rect height=\"217.44\" width=\"181.2\" x=\"26.925\" y=\"7.375219\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
@@ -5361,7 +5609,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 15,
    "id": "5c6174be",
    "metadata": {},
    "outputs": [],
@@ -5380,7 +5628,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 16,
    "id": "29a26710",
    "metadata": {},
    "outputs": [
@@ -5395,7 +5643,7 @@
        "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2022-11-09T16:07:06.672827</dc:date>\n",
+       "    <dc:date>2022-11-10T14:23:50.295823</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -5432,10 +5680,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"mad8a61676f\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"m333ce2bb61\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"53.59923\" xlink:href=\"#mad8a61676f\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"53.59923\" xlink:href=\"#m333ce2bb61\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -5471,7 +5719,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"109.392075\" xlink:href=\"#mad8a61676f\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"109.392075\" xlink:href=\"#m333ce2bb61\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -5500,7 +5748,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"165.18492\" xlink:href=\"#mad8a61676f\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"165.18492\" xlink:href=\"#m333ce2bb61\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -5539,7 +5787,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"220.977765\" xlink:href=\"#mad8a61676f\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"220.977765\" xlink:href=\"#m333ce2bb61\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -5586,7 +5834,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"276.77061\" xlink:href=\"#mad8a61676f\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"276.77061\" xlink:href=\"#m333ce2bb61\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -5620,7 +5868,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"332.563455\" xlink:href=\"#mad8a61676f\" y=\"224.64\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"332.563455\" xlink:href=\"#m333ce2bb61\" y=\"224.64\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -5781,15 +6029,15 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L -3.5 0 \n",
-       "\" id=\"meebc6a2b42\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"m4968efc281\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"43.78125\" xlink:href=\"#meebc6a2b42\" y=\"218.834548\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"43.78125\" xlink:href=\"#m4968efc281\" y=\"218.571172\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
        "      <!-- 0.0 -->\n",
-       "      <g transform=\"translate(20.878125 222.633766)scale(0.1 -0.1)\">\n",
+       "      <g transform=\"translate(20.878125 222.37039)scale(0.1 -0.1)\">\n",
        "       <defs>\n",
        "        <path d=\"M 684 794 \n",
        "L 1344 794 \n",
@@ -5808,12 +6056,12 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"43.78125\" xlink:href=\"#meebc6a2b42\" y=\"188.538556\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"43.78125\" xlink:href=\"#m4968efc281\" y=\"189.886194\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_9\">\n",
        "      <!-- 0.1 -->\n",
-       "      <g transform=\"translate(20.878125 192.337775)scale(0.1 -0.1)\">\n",
+       "      <g transform=\"translate(20.878125 193.685413)scale(0.1 -0.1)\">\n",
        "       <use xlink:href=\"#DejaVuSans-30\"/>\n",
        "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-2e\"/>\n",
        "       <use x=\"95.410156\" xlink:href=\"#DejaVuSans-31\"/>\n",
@@ -5823,12 +6071,12 @@
        "    <g id=\"ytick_3\">\n",
        "     <g id=\"line2d_9\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"43.78125\" xlink:href=\"#meebc6a2b42\" y=\"158.242564\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"43.78125\" xlink:href=\"#m4968efc281\" y=\"161.201216\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_10\">\n",
        "      <!-- 0.2 -->\n",
-       "      <g transform=\"translate(20.878125 162.041783)scale(0.1 -0.1)\">\n",
+       "      <g transform=\"translate(20.878125 165.000435)scale(0.1 -0.1)\">\n",
        "       <use xlink:href=\"#DejaVuSans-30\"/>\n",
        "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-2e\"/>\n",
        "       <use x=\"95.410156\" xlink:href=\"#DejaVuSans-32\"/>\n",
@@ -5838,12 +6086,12 @@
        "    <g id=\"ytick_4\">\n",
        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"43.78125\" xlink:href=\"#meebc6a2b42\" y=\"127.946573\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"43.78125\" xlink:href=\"#m4968efc281\" y=\"132.516238\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_11\">\n",
        "      <!-- 0.3 -->\n",
-       "      <g transform=\"translate(20.878125 131.745791)scale(0.1 -0.1)\">\n",
+       "      <g transform=\"translate(20.878125 136.315457)scale(0.1 -0.1)\">\n",
        "       <use xlink:href=\"#DejaVuSans-30\"/>\n",
        "       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-2e\"/>\n",
        "       <use x=\"95.410156\" xlink:href=\"#DejaVuSans-33\"/>\n",
@@ -5853,12 +6101,12 @@
        "    <g id=\"ytick_5\">\n",
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   },
   {
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+   "execution_count": 17,
    "id": "13660944",
    "metadata": {},
    "outputs": [
@@ -6480,8 +6755,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:200: RuntimeWarning: invalid value encountered in true_divide\n",
-      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:201: RuntimeWarning: invalid value encountered in true_divide\n"
+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:204: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:205: RuntimeWarning: invalid value encountered in true_divide\n"
      ]
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    ],
@@ -6502,6 +6777,66 @@
     "                                              angle_map,phi_bins,kappa_map,et_map)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "5e96e118",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map,ex_map,\n",
+    "                       kappa_radial,gammat_radial,r_bins):\n",
+    "    '''quickly plot the convergence, e1,e2, ex,et and radial profiles\n",
+    "    '''\n",
+    "    fig, ax = plt.subplots(2,3,figsize=[9,6])\n",
+    "    ax.ravel()\n",
+    "\n",
+    "    ax[0,0].imshow(kappa_map,origin = 'lower')\n",
+    "    ax[0,0].set_title(r'$\\kappa$')\n",
+    "\n",
+    "\n",
+    "    ax[0,1].imshow(e1_map,origin = 'lower')\n",
+    "    ax[0,1].set_title(r'$e_1$')\n",
+    "\n",
+    "\n",
+    "    ax[0,2].imshow(e2_map,origin = 'lower')\n",
+    "    ax[0,2].set_title(r'$e_2$')\n",
+    "\n",
+    "\n",
+    "    ax[1,0].imshow(et_map,origin = 'lower')\n",
+    "    ax[1,0].set_title(r'$e_t$')\n",
+    "\n",
+    "\n",
+    "    ax[1,1].imshow(ex_map,origin = 'lower')\n",
+    "    ax[1,1].set_title(r'$e_x$')\n",
+    "\n",
+    "\n",
+    "\n",
+    "    r_bins_mid = 0.5 * (r_bins[1:] + r_bins[:-1])\n",
+    "\n",
+    "    ax[1,2].plot(r_bins_mid, kappa_radial.mean(axis=-1), label=r'$\\kappa(r)$')\n",
+    "    ax[1,2].plot(r_bins_mid, gammat_radial.mean(axis=-1), label=r'$\\gamma_t(r)$')\n",
+    "\n",
+    "    plt.legend()\n",
+    "    plt.show()\n",
+    "\n",
+    "    fig,ax = plt.subplots(1,2)\n",
+    "\n",
+    "    ax[0].imshow(kappa_radial,origin='lower')\n",
+    "    ax[1].imshow(gammat_radial,origin='lower')\n",
+    "\n",
+    "    ax[0].set_ylabel('r')\n",
+    "    ax[0].set_xlabel('$\\phi$')\n",
+    "\n",
+    "    ax[1].set_ylabel('r')\n",
+    "    ax[1].set_xlabel('$\\phi$')\n",
+    "\n",
+    "    ax[0].set_title(r'$\\kappa$')\n",
+    "    ax[1].set_title(r'$\\gamma_t$')\n",
+    "\n",
+    "    plt.show()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "e9720a7d",
@@ -6512,7 +6847,7 @@
   },
   {
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+   "execution_count": 19,
    "id": "32772d61",
    "metadata": {},
    "outputs": [
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+       "   <g clip-path=\"url(#p3d99f1271a)\">\n",
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        "   </g>\n",
        "   <g id=\"matplotlib.axis_3\">\n",
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.678803\" xlink:href=\"#m2fa700b9ed\" y=\"170.024007\"/>\n",
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@@ -6928,7 +7263,7 @@
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"268.376413\" xlink:href=\"#m2fa700b9ed\" y=\"170.024007\"/>\n",
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        "     <g id=\"text_12\">\n",
@@ -6943,7 +7278,7 @@
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        "      <g>\n",
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        "     </g>\n",
        "     <g id=\"text_13\">\n",
@@ -6960,7 +7295,7 @@
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        "     <g id=\"text_14\">\n",
@@ -6973,7 +7308,7 @@
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@@ -6988,7 +7323,7 @@
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@@ -7018,7 +7353,7 @@
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        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m4dde90a54f\" y=\"54.484543\"/>\n",
        "      </g>\n",
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@@ -7033,7 +7368,7 @@
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        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m4dde90a54f\" y=\"25.635738\"/>\n",
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        "     <g id=\"text_19\">\n",
@@ -7117,15 +7452,15 @@
        "z\n",
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        "   </g>\n",
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-       "    <image height=\"148\" id=\"imagedaef3b22a5\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"387.781618\" xlink:href=\"data:image/png;base64,\n",
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\" y=\"-22.024007\"/>\n",
+       "   <g clip-path=\"url(#p97c804777a)\">\n",
+       "    <image height=\"148\" id=\"imagea573e650a1\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"387.781618\" xlink:href=\"data:image/png;base64,\n",
+       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y=\"-22.024007\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_5\">\n",
        "    <g id=\"xtick_7\">\n",
        "     <g id=\"line2d_19\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.925862\" xlink:href=\"#mf430b381ad\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.925862\" xlink:href=\"#m2fa700b9ed\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_21\">\n",
@@ -7138,7 +7473,7 @@
        "    <g id=\"xtick_8\">\n",
        "     <g id=\"line2d_20\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"445.623472\" xlink:href=\"#mf430b381ad\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"445.623472\" xlink:href=\"#m2fa700b9ed\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_22\">\n",
@@ -7153,7 +7488,7 @@
        "    <g id=\"xtick_9\">\n",
        "     <g id=\"line2d_21\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"503.321082\" xlink:href=\"#mf430b381ad\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"503.321082\" xlink:href=\"#m2fa700b9ed\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_23\">\n",
@@ -7170,7 +7505,7 @@
        "    <g id=\"ytick_13\">\n",
        "     <g id=\"line2d_22\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5d9a19782f\" y=\"169.879763\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m4dde90a54f\" y=\"169.879763\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_24\">\n",
@@ -7183,7 +7518,7 @@
        "    <g id=\"ytick_14\">\n",
        "     <g id=\"line2d_23\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5d9a19782f\" y=\"141.030958\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m4dde90a54f\" y=\"141.030958\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_25\">\n",
@@ -7198,7 +7533,7 @@
        "    <g id=\"ytick_15\">\n",
        "     <g id=\"line2d_24\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5d9a19782f\" y=\"112.182153\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m4dde90a54f\" y=\"112.182153\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_26\">\n",
@@ -7213,7 +7548,7 @@
        "    <g id=\"ytick_16\">\n",
        "     <g id=\"line2d_25\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5d9a19782f\" y=\"83.333348\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m4dde90a54f\" y=\"83.333348\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_27\">\n",
@@ -7228,7 +7563,7 @@
        "    <g id=\"ytick_17\">\n",
        "     <g id=\"line2d_26\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5d9a19782f\" y=\"54.484543\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m4dde90a54f\" y=\"54.484543\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_28\">\n",
@@ -7243,7 +7578,7 @@
        "    <g id=\"ytick_18\">\n",
        "     <g id=\"line2d_27\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5d9a19782f\" y=\"25.635738\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m4dde90a54f\" y=\"25.635738\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_29\">\n",
@@ -7293,15 +7628,15 @@
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p3a535c0c75)\">\n",
-       "    <image height=\"148\" id=\"image982aa41887\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
-       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\" y=\"-199.929462\"/>\n",
+       "   <g clip-path=\"url(#p3068c2f74f)\">\n",
+       "    <image height=\"148\" id=\"imagef29d121091\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
+       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y=\"-199.929462\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_7\">\n",
        "    <g id=\"xtick_10\">\n",
        "     <g id=\"line2d_28\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.431744\" xlink:href=\"#m2fa700b9ed\" y=\"347.929462\"/>\n",
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@@ -7314,7 +7649,7 @@
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"91.129354\" xlink:href=\"#m2fa700b9ed\" y=\"347.929462\"/>\n",
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@@ -7329,7 +7664,7 @@
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-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"148.826965\" xlink:href=\"#mf430b381ad\" y=\"347.929462\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"148.826965\" xlink:href=\"#m2fa700b9ed\" y=\"347.929462\"/>\n",
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@@ -7346,7 +7681,7 @@
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m4dde90a54f\" y=\"347.785218\"/>\n",
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@@ -7359,7 +7694,7 @@
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m4dde90a54f\" y=\"318.936413\"/>\n",
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@@ -7374,7 +7709,7 @@
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m4dde90a54f\" y=\"290.087608\"/>\n",
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@@ -7389,7 +7724,7 @@
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m4dde90a54f\" y=\"261.238802\"/>\n",
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@@ -7404,7 +7739,7 @@
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        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m4dde90a54f\" y=\"232.389997\"/>\n",
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@@ -7419,7 +7754,7 @@
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        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m5d9a19782f\" y=\"203.541192\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m4dde90a54f\" y=\"203.541192\"/>\n",
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@@ -7496,15 +7831,15 @@
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        "   </g>\n",
-       "   <g clip-path=\"url(#pc0b86d15dc)\">\n",
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\" y=\"-199.929462\"/>\n",
+       "   <g clip-path=\"url(#p2beec6880f)\">\n",
+       "    <image height=\"148\" id=\"image19ac4de295\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"210.534559\" xlink:href=\"data:image/png;base64,\n",
+       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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
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        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"m7e40f6817d\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
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        "      </defs>\n",
        "      <g>\n",
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        "     <g id=\"text_5\">\n",
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        "      </defs>\n",
        "      <g>\n",
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        "     <g id=\"line2d_7\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"40.603125\" xlink:href=\"#m8cc670f65c\" y=\"171.456307\"/>\n",
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        "     <g id=\"text_8\">\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"40.603125\" xlink:href=\"#m8cc670f65c\" y=\"141.019943\"/>\n",
        "      </g>\n",
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        "     <g id=\"text_9\">\n",
@@ -8379,7 +8716,7 @@
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        "     <g id=\"line2d_9\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"40.603125\" xlink:href=\"#md69d22a350\" y=\"110.58358\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"40.603125\" xlink:href=\"#m8cc670f65c\" y=\"110.58358\"/>\n",
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@@ -8518,7 +8855,7 @@
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@@ -8740,10 +9077,10 @@
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        " <defs>\n",
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+       "  <clipPath id=\"p4eefb6252c\">\n",
        "   <rect height=\"182.618182\" width=\"152.181818\" x=\"40.603125\" y=\"22.318125\"/>\n",
        "  </clipPath>\n",
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@@ -8760,7 +9097,7 @@
     }
    ],
    "source": [
-    "u.plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map,ex_map,\n",
+    "plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map,ex_map,\n",
     "                       kappa_radial,gammat_radial,r_bins)"
    ]
   },
@@ -8782,7 +9119,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 20,
    "id": "38b199f1",
    "metadata": {},
    "outputs": [],
@@ -8795,7 +9132,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 21,
    "id": "c17883c2",
    "metadata": {},
    "outputs": [
@@ -8803,9 +9140,9 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:174: RuntimeWarning: invalid value encountered in true_divide\n",
-      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:200: RuntimeWarning: invalid value encountered in true_divide\n",
-      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:201: RuntimeWarning: invalid value encountered in true_divide\n"
+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:178: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:204: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:205: RuntimeWarning: invalid value encountered in true_divide\n"
      ]
     }
    ],
@@ -8834,7 +9171,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 22,
    "id": "22ba0469",
    "metadata": {},
    "outputs": [
@@ -8849,7 +9186,7 @@
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        "   <cc:Work>\n",
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-       "    <dc:date>2022-11-09T16:11:39.719159</dc:date>\n",
+       "    <dc:date>2022-11-10T14:27:07.045933</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -8880,8 +9217,8 @@
        "z\n",
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        "      <g>\n",
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        "      <g>\n",
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        "   </g>\n",
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+       "   <g clip-path=\"url(#p8117d04e4b)\">\n",
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hddmt13mcLvtNu9y0q+hq4zIruh+AqS9Q7PLSxuJ2qrT2qo540KxOi1oFc9UCQcP2HLpEgmEWFrctUPmzvQYVBQNzO6GGdHalepAi+1PTlBe9bCVAeXTfF6iYlgMefNnBFCA9axHM85uu+00jhA+YpCrTCzBNoMS2jrPCnKALaIrFlftftQvieoZy8qpuKFJRKwdjssBaBZZlgkrKda0ABTYfQEUDQyVkOyEHkmG2x6Xyq3mKS1hn0Kj+WPK4vrC+cWDiolSbZQdTtbpdi6BP4XvOTStMvVR0oz1Q+0yfhKkv257BdGVxS1a62jaHctXsfE9qRAWbxQJrrkrbC2VqC1RJiL4Old9FAHADVMhVQ3Jueh/8TXkqWwk4W98NfW4lFFUCMGwQyNmbdfwu4dpYXW0RTFN5a4tA58wUZ5aTkpuiPSAVpP4JmPqmLfBqXtplrFMw1xNUplCZn3wXh1olQMXiTpWeHza1y1Uo8E2OZ/BeQkUzVLGmpLCazY7JIyIL6b2olatUdwuMVkJY31XVF6pUQRq2N/6jOo+85qZnVV1Y3Xr+gapOEtNTantAeDQu+wKTPIGpj+vk15+G7wWkfW6q8CxKpZp/46DuqqQEtKJWSwCfOui+l+dK7wxAXZTHP5ZQvapUaX2mTEJUKj9kSI88Vcf7VuurZ3WJhmdYX8PoNSVIi+1NswyK3dWqbneWlGp129y0rehgjcs1M7lSJUy9TM+tMPU9IE9h2ljc/Bx6hqobH5AM5QQ7ZU+FiTJLkdJ4X7Xe5vCExfltk+1lMMfUVqhhfZ+zzvanJZxJ2t4I6ZmnfLFKb7a+qwHk1fomqJal5iYAp6ruNPC7WF0Xxr30m9YQLmIQZRe8dMJfgqkXcGLnd1xAda1MMzy2fyf767NSQRUHP9S61YgxNU21GjbnO7UG9lLlzR/ikquWZbVM34pUwwZ741aoSBFByTgM1RqV3+5ZiQySyfqk5ekXn1lffaFTrsKcm66s7jxWNxqXNTc9up+lt59nD2RFV6ehbGAa1Rs9Aec5TM+qvLNS6aRKeXtXVyh7t+yESK5WAIFkwFYDu8GxWGCFJnKVjgpxYIhxJR9DEPj43xVUrUIVKgUglYqmkB55KloJs/VxBvR1rC9h8ss4wVksK0xPg/gHVrfthEevqfMMU38OE6eChQUtME2gfaBKq8VN0MzAQQ2kuH3qQwEFGl3XC0jVAkPRHJyrXDVgi489sldlwvciVOIvKVSKYAG2hPQ1T1Xrs5OM8WVAt3HC7HKdJFXK/zOdk2kTxPNAg6sWwTJGp2VYZYzPfQKmpWGZGeqVvBQ2ttz3BJbMqoSy3SbYPTQdI3e4q5WCfPKU7dwpY5X+VCjaCaPIVbuwnvY5rjN8UDmA2wb16SFFpcaSdufjfZP1SQwsW0BfZyRAJa2vkQX3aHzWzJSnb97MJJiHV85Wl/2m7lYXLYO+2JzQHqZJdZaG5TO76xf9pdX+JssrwTsBm1XJbjcnOCCuCqrjHIDlyJaxToWSswUmcEp5LiIsKjaF9WUZsK3YvAiVV35Eoy/FV9bnahUzEmoHvZFXetXyVlVyqwNw6ohPQfzC6iI3ZQj3XlO2Bv4eMNVg/iQvnYdXnlvcpErqIxMOF0RxUBfPTT57UmCW4+q0zVDFAhFVYAbuWa3qrj+F9RWuWNdPQEX+knrMoBx56tHZlcqgOkgmNQmYMlgXlfK+w9by6lEtc3aihGqcnnCFqTYvR0W3Ni4/hCmu1x7TC5XcpSpFHjrddg7emNbV76sOVGSo2KFpf6W5eWGBWKvABGPOVVDsw3pFRgFpyNNfJkS6XK9QEYAeWw0mBaN3U6ZOBOpmcQSgMc8q5TCtKgXiOqXvZHnAeT5UBWlSp2J1jz7PINDaHsgA/gSmzXUowKtK9TMwW4vbKNNUxV1YXEIWaqUDroMeAm0EsgE92NkuEacd9325t8CpCoydX/pXFbLLaw6ba0Lpd/nzal6ZoSJ7Y3W6O/nRWBa04xH3riBS3Hs7BXTeqFR89wtwYXk+hWWnTg8995y6Eu6dN7mpjNFVZbqA5wRWgeUE1UcwbcF6UsVdWBx18XWxtgEkPoMx6PoDFhiV3gIS6Thfeeaq/Bm5KmGqFjiTMkOlcZPP+oy7+tEyMZBMvp9sKCamttjsAuG9/VWVCuurx+VVq9upU1pnKFNpEWRuigHf2h5ImwPoQXuL6+V6BuUdVB9b3LnXVFTpExZnKua3idjQi8K/k4V55G6M/Xe1nruzNEIHSEtroSjSUCVD4gQTsBkDrCo4XswEVQemZmdXy1LEoG5AdbJqrwl/qFKx9CVHAR+rUwZxt7oYp4vcJB/BVFUorm8y0i58n9RqhecUxpdGZahW13G/XuApcKErSCShGgpF8E4Q2zCM71ElDI7qTs51Km2DJ62FzZCNgbTJVStcgZQSpJ1pPysVeeVX8xSn9bFff5DiqKqydM9DpQKunTr1AtV0UgsfXgmrG+N0fKroLmHqmx7T5fqLFjfBFbB8YHG7vCTi28Ut0BUK3eSciDw/meX5eXCRucpVh3I/OjTF9s4w6cethQpcVbGEKHpN8ecM+6dQEXmcs8qvk9o5ad36HqQZ0B9kKmVg8dQ9ryDVZe2Kj77TUKdpKq+M3KSfhKm2BUJ5ziH8x1sCq1KtjUpMKjXnpVWh0MUUyolyLIZCTbmqTk8ZaR2j9V3GApfWQlqg4sPWQs1V0bcKSxw9z2uoQAAekaXM/qiP4ZiwPo6ArozDO9rNG55HFrcEEOdpEas6AZhASnVSxr07WG51UwgPm3vYLIePYNqp0Wfz0tbiEiD8cF4aCuVAWYaS/FTnrikKFZY3IbDLVZ/trn/QWrCuOc4h3ddZrase08Tri9JDge4HkxJBKPKU9aWaKDrbSfQbMR7UcLD4oK5bGWna3XxezajwZssbswpKzymrujqDICo6B6nAxAHQKUPtrO7nLW7XEtjlpYSpWNtQKDG41Co+z1BImzAJoEmhopWQ1dUuV/1Ad/1pFRhhfwVqylepqVDMfaJxdzvAIfIUs+LRFUSmSJ2HRR3EEJ8nJUpoZACt1lfDeHwTVKiTzSJo1nOKFoEw5EHQBwMPt7oC0wCpwPQUKMU2oP/owO5HeWkTvk2hAq6iUJGhwIxUq+g4g6HNZG0K63mcHUa/aperPjPAXNUrNxcLbMjLiZqETvNVT1AR3PrcDcmDuQjuwmhFpR4suK3hHH3KUGsYn7JTznOi2eoePM0e2ML02IN0zk16VqsE4nMWt81Liuvw/QFMlqF6HzvoCqpaAa5hnZ7kqmgtXFlgBWIazsGlBbJ/YIbVzX93gor8z8IDOvlYH1sYb2zNzoMlp5rcpfkZROzZtwrlYfy+yU45Vhcwhc2FMvUFpsdZlSbFSnh+rFG5tTi3tV1eWsP3rpK7ggm94zA5+wAqZmjHXAF6WNdm1VJO8fUdOV/uYIoWgo6xwI8aoW22QHaw4r72bexugUoJnCkVeysBgKtUY0arWaqO9y22F8vaJZ+GV9TGDx+d8Xi4Qj3YAniAdCfww5uWD9j6Cs9qcU+quHr9lRmVu7x0gqmG71SuAo7npRUmqOLQLqDGI2CtUPkbGFDBx9vMCu3zmsoS7/uaq9z2sgosjdBpLLDCcxHYpS0WqPaa4n4MgqgCR1SDoVD2wpQAYUXviju7SpG6SjU8VHD3yi9sb67yfCjFJ9A9/KQYlpuaqZTnJr2CyZWJO7lCXVscO0yvBu+hOjjNqDzNEkgVu6jkXoXJP9HaBQdUXH0AtHaGqnFuu4LKcRgV4ZqrVgskhynGAnXkrY/Uir2yYyW/PFsg62grTFDBrY9t6JdZ8U7NjtPrzY7R41Hphe2tS5643hUq2gTvD4OpPxrkztCwufsGpqJMlxb3JHg/U6WA6tLiNnnpp2DqHdoF0AjlzXYc9W5QifrHo0Dl205Q1UIuwjoTtOvlaRZTuQK46TCtF9WKrQFJ8dJKvhIdbQXRFSpXKVI8Hmyn/+mMg/0IX2kQ7pPtxfkN5urOz1nggTw64o+H5yZXpwmmB8APZACfq7u/gyotYfypxRWYTgCtMCVoBSbRAZOq7fhQKJ+pAW3NAph/tgOqfJIlU6G5IhXAEirCyFU7C1TLUxHYX1IrscpQ20atJph8PZsfBSoyqIRs/cEKduu7tY53aXjLSXSUTc5Yqt29i1ncu1vd/d5cnRpw59nmCkz8wIU6LaoU6/pjqrSzuCkvXamRAGsAH29w2SZiMPXuaiWRoXxHig8U59tn1dxQqQ1UrCfVAmmG9bS5qkjpiYtaebbK4Znl62eJig2yAatFraAAl/8dfl84lKhB3RueD7aB4QcL3nvDG3cv/5sH9DLHPK2uHLkSHXG3O7kzcPfM9E7gO80gPQpEj7Mq7Q4mmMr/sp4VnO5VabK4kpemSu5FmIY6FZhkhHGLTjH0QmQaiqDCH0Rk5DW+hkpoo1r+OKZxAInCwBW3PiYgDzJ1tfJslUFMyZQu+lbRL11t0I+rUwG0Ufx/DpL9Tc0Hj4HjCOgPanhnxdEE763hizY8dPSf1irP1OkYCvU48Lg3h4lBd55g4juB7gOkqlC0Bek1e7tUpbq95qUavn8Epmp5AVdCpt7YVIWqWn6CpWztGJUfkJfRHnA/maHyWZGTaolvY4MscpU2cvVytbLafFxnbG3Qbg5g1FWKilI5fIL85qUJrLDTVCqDqrNVfN/5MNvrDV+b5yVQOnZcjzD+3hu+3w+3Ooa+twHT+4CJ7zNIdrmAtM4aWJVotbdSwUUmyuCdKqQjL60wVYDyuQpMvp3Kev2JEA7RkqN0KJQyg1TgZ1O1kC6eoSR2sv2zGnOFBDNIkamqagVUtMlVnmOAUC0Mi6SNDZavTSPaVIM+J06bAQch6GE7Q45Qt6g6DSqzvobOwL0J3h8HvreO937ga7tPOcq+3pXw3g987wfeHwfuD89N35tZ3XeH6T5g4kdRpcdzezvlpKo2xd4+VKVNXrqEqYbxK5hSjWSE8LC6BFFwqBbJC+tjuGKU7Q4PgGF/Vb0+goodlJqr4qx4VZ1KtjIIZ5hSpSg+uZGnimKJ9amaqKnzQaNi8seQWrIDrOHZGbiT4vvR8XY0vHvFhzZ/1/pD7Lb33vD90XB/P9C/N+Cdwd8Y7Z3A7ygKVXLTQ6c+08sgFaWKKveUleKDtstLr8JUfqj0lypMV1YXTncYOKZEBpcgSrWc/7RYX+58YKhXQKVl/QIqQEeuKsp0ylZUwAp1fBGsuA4xtaIGSD0jiZSuu1d9nRu+txtureMPt1YO2Iy2gVV33/uBb/cD37/f0N8b8L3A9J3QvmOG6aFzVfezIH2kSn6/D2HSBaaqSLG/V6sLdZKiTsUqjwmcjUrZzrmwvpqnMmhEX+kFqGCnoIY8UatXwBKrCGP7CpaIqSeJ+rmW4G9+BcugejTB99sNf7s/8MfjwONgfAl1Uja7exz4fr/h8d6g3xr4b4z2ndC+uTrdy09X64anKs0grRnpVZB2qvRZmOIxn7K6uB5i4m2mAO1QUc8rArR2UinvehaFKupU1wVA8wMZdlCRA/QBVNl2J7wGFlne0ubrEdYp4FLv6pNBdZjtSCeIt0/i9DcPMIQOfGuK348H/na74ddbg/gBsHdp+Nvjht/fb/j27Qb5/QD/zjj+NmBqCZSOAC5YxuNG+T/6QTMkL4MU7/0zmMIGF5iogrFTptzn9VLyMo/ydnVSUeT30WeWij9AOqqvRvag6KKz7dis+lB2foWIXW3KC7qCyuTUnzfPOFwODu0XYJXwThSq5DDF6yOrMO24PxuyoVCOB9m8cz8pxQMW0H8/Ov76dsf/9GXMl3mXhr/e3/D7tzf0v97Af204ficcv7vNvRtIUwgXTZu7srWXQMIGpgpSgrCBKQXgAq4CEUm5HuvR7M7r5bawQV+sU64ExNevBjjxpN4HIrpQJhRgwvqmUyjqDNgFVLl9tcB4DTFF2avGE1jeHJ1Uy0M6yL/dvSMbovwA5CDIwwDod0qluqPh+/GGv7w98O2XW34lx7d+w1++fcH3v76B/9Jw+81h+hvQ3rVUdLptA5x6SAUi4AzS2FbuiwuLq8CtMFWA6rJaWAFrXde6LZYcVQG8VzMUKsN5wnRhe3FftwEqKvAcog+govGmThYIzGrllngCC5hVCwGX35/HpTKgriLSAH0n8Lt6mW9d7nfc8NvtK/78h6/4py+/AQD+/P0rfvvtK/i/3vD23xi3v8Jg+q5od1M9rs3KZ0qUAIydtAPJ1ovyAD8O0wdwpTrFPi63DSawtbtYDrvdqqDxeDeatLvF9uKPLBD5v49PLatSEU1Q2ejPfKBU2mC8dsC68vA301/XGa6hXCCHygN8eyf0d6B/B9p3At8Z3/AF//r1V/zzH/87AOBf//wr8K9f8PX/Yrz9BWh/U7R3oN11zkglXF9CVN6zE0jADNAVTFjuWyF4dblSrlh2drd7Gt9+ZOjdPdnVC6i5iBaASsZ6+hxwlZr+tv+qz79ABSrrwBYsqFvcClfYYofbqD+YAG0GlXwD5HfC8VfC8Y3xG37Ff/nHPwEAvv/Lr/j1Xxhv/11xfFPwQ0fl1oFVUcb/dAFRvF+YQcrniLdjgWl6H5fdtc1Nu+UKwPX5P3qO5fqxv+ffYQnbKxlr2N757qT1C67d+uJqbUu45eX987rfXxR50n7CBG88Pob18rCMhExtrh4Rbr8DX/5M+PJ/M/4z/hlQ4N/+b4S33/rISGWnT5fArCDA9OZ/BqZcSlxZn5uudvyrdvfZ5YkSbnbt/79sl086uX7y/v9fWf7HKRTRpDh5/QJhXSxy2iH1MSE05QuGpvszzddpvT4u63NoA5QJ0qz6e3wlvP8j4bf/KPhP//P/AQD4z/hn/PovDW//7TXLywkOqApZ7Jgtnw57hj9uVLepUt71j/+lqlTef13YHCHfStZx/WdUKkYzNstxyjrPss96++6+dtq4j5+D6Pwpps3zx5Ah0QzTBqQtRCtAteKjMq+qEfqN0N+A/gvh/U/At38n+Pof/4J//8tfAAD/53/4Db/hV3z9ynj7Cz0J5TiF8tx/utixz5GPUJuZsLZMYp1hmTKeLOaSTXDN8D7dB4wzGLQ+/5Nlw84BAMS0bPfrvF5yvdP5yT96AbuFaQAygXCGaVKUFaQVogW+0ZPC6KS3oUhyAP0Lof8C3P8IvP8bAf7pO/7pT3/FLz5A/O/+4Tf87/90wzd8gdwYt796D+o7wA8aitUxd8JlgQu2nnBhD9YoPPQEVVa08X7ApkN/utJbGs9jm19ntkl08Z2G+d2Gy9OwjUQMy2NagOHlssBSANSdIlV7SzVar2OGKZ6vwDQDRJcgTXZGFxCV62ZvAyS5Af3NYHr8QXH/k0L+8Y5/+PUb/uHLN/tSQQD/8OUbfv31G/58Z7zjBj0Ix40gfyNvbNLSJXc7FJpU66Rc8Q/UAsNnZRhwow9nu0QHVNFkLlBZxRsioK/Znqs1hWJVW8shMIaNX9kh/Qogp4g7ZAeIBzRxh/JH7ILG9d16XH8ZLnyoTJMqVXtbQdpAZJeUEMWbJW0AJYf/3Aj9CyBvBtPjjwr5tePLH9/xp6/f8bXd80usv7Y7/vT1O77/8cD3B+OOlpDKzYdf7upqNaCah14oG54252wD1wIWAVnRZk9uhcqJ/BCqVYkim602t7SE7JQEsW1RL8AYotI2oAoI07XdFWhSnRbIJoDqi7+A6SVV+giktihTQFUykjS/XzOQTJkcpl8U/ReF/KGj/fGOP3x9xx9v73jjoe9v3PHH2zt+/3qzOeRiY38goDUDtb0T9A5oDg6XscOcPqMgppyxYdN06RIsKKwBjFmtyI8Q0oDV77GFCgWYVbVK7y9Vqmasne2pKxjRgA3AQQGPA2NgXdjdM6XK6mpVo3H9JZheBclhqeG6bh8/DhIDegDSDKT8eQP6V0X/qpBfBPyHB75+veMPb3f8ctxx4478wmvu+OWw296/Hvhb9+nAYCgDzf82N4CbzdbU5oPQjcr0lTovy5WKAiYq2/dg5baw0ZNabaC6sj5VjK/nxaxMsT5dXtseKZnljRDOQ50cEvvyaJ4tjWhWp2l9AxPz6zAxvQ7SxtYqSGlzoUqHTQmWGzyEA/JF0b8o5KuAvnbcvjzw5XbHL7c73tqjfIeufZ/uW3vgy2H3ub81+547e1fzNYHg/zegDwLHFBqGHS08TbALpSpZi+wMzK+ARXJlgQtUbN62QpX5LawvspSMfQM1BkjjmIKyXU29iAhKjCPVyaWrqlPa4PqzKlMF6FWY+FqVtMVz/BxICKAOr+ZurlIHIG9q6vRFIV8E+CJobx1vbw98vT1w446DBOw/AMAkOEjwpdl97l/ukM54CA2o4K/x3XeM57aYApyHO27AsnxtMzteAqu7uoRaETx3ORAvQKW+SxKqrHB03td+SQB0VakQHVUcCc1GnXL7Ck7jE2RKZAPIz2Di11QpP+VhZ+11kOJAUIPKFGkO4YDc1C4DpjdB+9Jxe3vgy9Hx1jreuGd1V5eD7ba31vHl6Hi8PaBKdt4t3ysKm5qsTJYECMADVlr7QQrC8ND+CbA69pXhRq3Uyr6y7QKqhnEqggKP+qFz/kny4S+2weLIUFWlxE6gchhIoUYBCn/K6j6EKe/nILRFldpibxW2dpGRaAGpYbm0lkDApG2B6U2hbwrcFPylox0dt6Pj7XjgS3vgrT3QSLPCA5DX35rd5/1oeD/sAE/9AogSVNXBcrkohQI/3AAeZCE9oQKoe44i9TzlHyoxBTALWsI7ilpl47SoldssKXIOwIdQlTwV6ri1Pj+Fd6pUKFRaXWsOCNsxeRurO8HEfIap2tUKU6O9KqVyDXU6NSKLOp0UaQFpZKZyeThMx4BJbwJ662iH4Hbr+HJ7mDo1tzvYlw7FifDr9bjfl9sDPb7j7q179R2nDhpQ0d13MselKw65MhGmTEXiYBWVgvh8L7H1AA5K81SjUKtolnavDXmBirSA5CHdYZvyVKhhtb42jhwHGqh36FCoAKThZHUOV9pc3v85THb/eFHD4qZGY9y/VmvV3pbyf4JrZ28lgGuL/BRAFZhuCj0EuAn4Jjhupky3sDrqdmLXok4GlV0eJDjI7vve7LHxJUBdyC2Jh1LBZ7w+fJ9MZmBgxbe5w6fWDBhdXcjmcuWUHIohFxozL8QfW7OVwHKc56qcDNnFwnuoU1WtgApmZWl/cSaean32XXRpGYep0bA2cgtMcD4L06JCmZc8RynjlJXystjbhzlpAopmiKpCOUihUAaTW91NcBzdfprgrXU0Fhws1i4ogdygGiH9YEFje8y9NRxHN+u7UVoffLfAYYArDqrQO0BCNFQpWwojNyVkAih5vlpsEDkijZGtIkthyVV+ZHie4CSgCtW6gooJUXzYR8WnxRKDWnTKGwOtjdxUwBn/+SdgqiV/G9BsVSkhed3ewEOVspJblaltYDoCJgHfLDcdh5gytY6DxRXK7K7mp1gaKW4keJDd984Nb62jC0Fu7OrkzgO2dSDP/uKnws3UIBNc9n+zH5ChcZss+SrsbrVBh3JSqwoZYc5VPrt7ggo4qVZAlRyUCWqkCo1ZvB044AqVOarko1SnK5gSDrrMS0N9/gepEm9AaoAcOiq8gOmmwCGgm4Cb4jhMZW5tqNLBw+4iL8UZ7OBfIxu3H9xxc6huTfDoguMg+5apm/iESk6lYpADpGCihCkqQXF1SrVK+zvbYJybSD2DIYqACOqrWpXLzFVMCRXEFUdxVi1XoaFSYxta5CcGQqHIFSozU4XpKoBfwRR5abW4DOEjK/2sKk3qFGAdgLQLmJracXmHoB0drQneDlOmmyuUwTJb3boM69N87EMYb4efqOzo5jhi1hf7M6CydYMqtlcL1GdqRS+qVWSrBAyLBeJ0JmeF56xVtWLYrcsCFfzsPM0e3xEZivYwPVMmbwtE+E6gXrG4H1GlqOAYJ2WaVCqUiReba65Oh4BZ0JpD1DpuraN50D5IcCOxb1UgGeoEoMG+PraB0vYO6mjUcGsdXQm3+EJqIehBWfXVaeEMckXSXEdmKduZ49JbDJNSvahW3cf9NLYtykWzctkfkedQiX1ATlB55WcT7Fp7CSZlnnpMO5ieWdyzCu6ZKk0wrRZXwXJlEs9PK0x8GEjHITia/TRXmfhZ7c4UyQO2+immvdrj8tiu/lxN0MUO74+utjWteVIqepA3zXWoTi8WGD3VgCcOdP1IrUJ+fD0aok8tMHJVhHX4t5NBACEQ5JSpTlABflrpj2BKhSkwreG75KWtxZXgfQ7jG8tr8/ZLi6swHVpaBWpwtYBJQU3BTcHNofKKbqiTwRTVXSxr68DO42HqdeNu3xXjahUqdTS3vvimcx1H10ZoN7D83FM5/7cAt1og3M6oqFUsVa0ikKM0RFEC+84C/SVoXjJs9kIg79+uo8htV1AdW5iy91Rg2lVym7xULW4K3lNGetJXWoP3anErSE2XvpPDFMrUFNRMnTjUicXOqVmU6Viqu2p3VaGq7TG8J8UdhzK6Cm4s6Mw4WNzyaIyOKJtQFBbGCc0KEGXEZ7XAhCdhQlpePLOGesXszXyM256U9Wirr7kqKkA7hs2gEjErfALVYYoT4XuBabK7AlGo0SYvPbW4F4P31uK2QBVV2sF0qGWmQzM3NTaru7lChTqZ3cml3cV62N6o9hxIMZUK1VO1k5M1P0UjDoIgTst/hsrFfOzgYCSUqF5SsbadBeY04AWgpDnWS4hachUBYy5eQAYfdomPgb83VlTafK1Di0Kh8cna1kruMi89sbhPBe/F4q6USUKZYluFieHK5FbHgtY0gTKQdFKnqkyhTgFTPfE9ewNHiOx+ZF85W1WqC3uD1N8nJUAlm4kxuKtHxYqK1XkF2Keb8/LSAvOnWGBRr0sLJMI4+UX5mzr+dCLptjfyVdzXwvoxqdJibVP4/igv1Wx0YXHX+WmxuAJR5qZQsCcwwSHEIcPquOQmV6djk53C8tqiSGuVBxpfYt18GKZvspQo2XCQBlSAKkGamPVB7FsWGjAaCzVH5XeApQJxWQ/4Uq1OS0BU1GtjgVMVCGxzVT6mhPX1S89DzjJDbSu5F/LS383iaqPyQpkMrmuYMoRXdWrD6tjV6eBhcxUkjgHhzTievdeU1xlhe6ZSBwnEVUqV0P379zoTmvr/plRsY3yqY1LvJVSxr2O/Yr1rDeWLBYYi5f0wWeBUBV7lqlSzEdanCtD/JwNqreRq+L7KS7UlwJgalU+rOMamkqMlO11AFZmpbn8CE7eRm5g1O+I3HrYX6hSA1DAe6nQCy74qAk3ncJ5tBBIIE5oKbqlO/kVEzSolND9hbFR+z6AitXNXrcuar2hYIBeEXrbAgFL8SRlz6yIelTZYFWpUgEda28/kpaVR+VIVd5WXAhbawFRhW2HiUtGV3MSsaXUVpKpOtxhu2agTADRvI9RvR59VytoNomRf6wFClwCLcIT1KaE1hxL2ZY8x3reFKqFZgvrMXMlVgLpmZK6ScqerKjBgikZobS0A1+sR1tm+dV4hRaGu8tKrLYFUnzNYlxZXtp+gmtRJz+sXMFFT+5S2YXG8BPHGs7UxRv9pVaeAaYDFJ5W6cYd0mtWOBQfsq2KFZVifIu3PTqEUmWoDVa/kVEsqoBSYplx1ZYGEGaSlEbraohL8WD3bTuJMZQ6bc9WhB28tblRr1y2B01hcgLCxvC1MDWeoJmXSS7DAK0wKYp1CeGSnm3fEM4i/oE4VpuhxCyihsilHz1VKlNDYvn/v1iR7UoABZSoFoA1dUgDxHTcTSLFOoSi+5QRTPG4o0lhbbgv4iu3VsUBctBYIGP0q//Ym+6JOxfH/RktgX+FtYJpCeYEpuuBUA7irU81NPhRyCuJUBoIv1CkWLrsipp4Ao+LbqdTBAlH7qjTVniCl9bFmnlqbhHAFs925qFPszXKdun0Qp7Ae9yu5attamA5bp3ks8ElrIU7cli8tFsk+1A9Y3EaZLlsCr4TvVB1A+QWYXJnA9kPPchOZBRHtbG5Wp2p1FtSXWQfKpvtufUJ0Vqlif+R/25RLoM0n4LFanoJAYOeIhyJPdTo0YgNVXA+K6kuk+W7jOV5oLUi530V3/SMLPFKdXuh6/8h0k11e2gH3QzDVio7c7ja5qW3UKZqZqzoBOMF0sjyHSrQZfItKHWl5oVLkX+xIUBYcAY3Ch2Psf5Flt78EFegSl5qfpiGbNVd90FpwYnBlgTF4TQAOPS4alZ+xOPokTAEMjevRY0qw6BMwsZxyU/NWQXTDZ6gioPetOu1givUK1dQ1d5U6uEOEsn0gapcHqIzrEVRlAwG/DlVmqLlXFUxMpf50g5ahlIW+H+iuq6uUv3zLULu5Sz86sDu2l9uW8J0wTd3wF2ByyMEAsYVwohLGPTcFTKFONYjn+Nsy5ymhojk/7Swvc5RbH0OnvtRBgk4EJi5qNVRKWMYsBNacjUBqh1ZBgfieP8tUeoaqE+J7daIBmkISX86EolArVLFWc1WxvE8PMHu4P2wG5KJK9JrFzfAst13Z2jaQvwhTmT1Aba7omMP2rq0uGo+3mHG5qFO1ukml/FKUJ8sb1kdLlhLciCBkkB20tz5R2LeRckxv8f6U/TXEQDI6vQQVVXJi1nIiUsCpYf00MbVWejgBNFWB0Qgtgf349IzKTfBGta9XKrkFprC8LUy8wMT1R4YysfjsyzolZe6I1zbBTp1WmNZpwNP1AlU+tqiU1DYCDQus1ndeGKo+TqZADM0kVHwN1Vr95cs8KVQFbTa+Ec7HPaoFfjQjVAnRNhiqNFVqZf1kcbRTnefhO58jLbDAVK5PMPk6AqJUJ8kQnqpUctNqdTWIs0/dvXlAD3XawdSWXd9BA6xQKLe07AAAZnk6AjqAyfpiqXkqQ7pXftlOKBKj2EAlNZjPGSuENCnyn1NYp1Kx5X2ptApKFVjsMccCXa2OrO6KKp2h2lvcNi89g2lqFbwIU2kLUBMQIyu6DOGb3LSzugjitzKG1yDTKXsCpgDpdLBC7J20wZbVIvyIFYYdagXGCOiL9YFxylNoJd2qOnhzj+oSKmygcjBiim9dZm3a5KoyZDNZYGmEng6RJ+C4UqUJlsn+VlhosrztmNxpuy7bnsDk1ZwpFMAspxC+9psOOlvdsyBerW4HU1wPdRJl20YC/sD6IqAfNFufyOiiK4esMWpI59KjWgFQaJ4ucQsVFahQACmb5ny1z1WjiovMFNtLYFd/Js0qr0BVgNkp1St5aark6vUyW2ALE59hCoXiNiq6bQgvuYlIT1ZXg/jNVWtndbFUsGLJ6w4VgLkvFZZGhBs67BvVLaCDcbI+E6KRp2pIBwQdNi2EWxkdWaHCB0pFmLf51N7Z9lBaCQWzqlTV5ibIgHpCj2OoSFGlbXaa16+qvC1MEb4/gqnNNpdWx3XAd4TwmptOLYLF6pjMhqJ1cKOeVldzUysqdXls3lLlxbZqfXc0Ox2QAEKmaKv1QZBVH0KtdNheVH7SOU/bNazvVagCrAUqXm1vcKORq3K8DpMF5ovw7alWVBQqAViUap+bNnmJFpjqIG6Badr2DKZS0fFU0Z1D+Dk3jcuwurUjXq3uGUx1XA+IacDn1oHtJ9paX0AW1mf5SVKhDC7OPGVNAJRj+gQc7QRdIbiGal5KWCdkr2pYJIZqTY1N7C1wbWyOPtR4onN2wt7idrloo2I/DVNCNWCqIfxofcAUQy7RAZ8C+LC6XVW3g2k94mW8o7XBM0MVeWqt+k7WJ5Qd9ZjmAviM0GZHV9aQrmppKo6PCTw+gsqK+hmqaZsU29v2rWj22qpUQWGolSLaBsCVKq3BHBfgfAhTqwp2AROFzWHqNdWKLkL4Or/pWKxuHV6pVlerOrOoxxam9QCFse/Ce+QMFT9wl+NU9YX11arPVKpntRdqBWFE09PWR8PTKr+xf7WEYfAHUKVgzVBNbYXEc9hcPt/GAle1OofyTfCuFneyv9P99ip0BVMMo8Q0FDC8NeDjdEtuGiH8ot8U01J8hz6r6m5kc6OuYJoOTnDN78rTiTN2UInf9+4Dx7uqDwwfRJbMUXnpvIjvNU7YHKzONm8MwOimazndsz3DCaoI4x9BNdleIewUyAfYpk5LKD+pUljganGr3W3tTzfZ6gxTzmnyxw9lMqup7QGO0L3JTaM1MA68HFCNBubN18PurNrbwzSP6RU/GPtkC9Utd3W5s1tfrMeMhFSwDOsOHimEo6kpRakMLE74FKgnxBD1uVT0HCoC4hxTmakKJLPtlduqBTpYGdg9oh27rBSqVOHa2t3fC6bMTOLnPltgugjhXPJTtAimag7nsboK0jOYeFKo8JjysY13fQMVgyaw1rG+Wv0dXAI9MOepJaRH5We9RDVFqo1P0GtQZRgf4T0hqrdPtldgq5Pz4ikcqmOrSjsbW+0OPwETV2UyeKJxWdsDLeaFL53wZ7nplm2B6D/1bBHcaAy9NOgEUyiX7bb5+LzJ5mJxiJr3i/KNVbbd7yH9Rv2kUAHTrWarJ3kqWwg8P4l0tuwUjc8IS/490D8Dlbad7eXTACgd9AAtgDqp0mWWmtdnyD4BU2leUh2no017oHbCX8xNVy2CGsKH3Q2YQpXakqHG2F19gxlTxRe3E0ydtE0h/aqV8EqeApAh3VQLqHZIleeCRu1IfQqqsLMa1jNwDbCyU68jWx0xhrdCsrW7krVm4H4MpmxebntNS0V30W9ac9M68JsKVUL4FUwVpNrUrB3y+gY3gquTXEIl08cck1rVAeSap1KheFgfANyBqfJb2wmav34CqgqMDBZIVtvz+0VgVyPsOKnSM7BWmLwtcIbvyuYwwUTTdJRSzS0VHZFiN063y03rwG/kpnN22sO0m2WQAb1+ZKtq0R6qU5Za8lQMIJ/ylPenhmIxxG3/XPnZs0v0qKbGp+1om/byIlSKcwWIcp9S2dVLUvsQHCd4dhYHTIq0NiwjQnwM06xKa6/pw4qu2B4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y=\"-22.024007\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_3\">\n",
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.678803\" xlink:href=\"#m72ce32f50b\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_11\">\n",
@@ -9250,7 +9587,7 @@
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        "     <g id=\"line2d_11\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"268.376413\" xlink:href=\"#m9124cecd13\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"268.376413\" xlink:href=\"#m72ce32f50b\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_12\">\n",
@@ -9265,7 +9602,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_12\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"326.074023\" xlink:href=\"#m9124cecd13\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"326.074023\" xlink:href=\"#m72ce32f50b\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_13\">\n",
@@ -9282,7 +9619,7 @@
        "    <g id=\"ytick_7\">\n",
        "     <g id=\"line2d_13\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m1b5f838c68\" y=\"169.879763\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"169.879763\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_14\">\n",
@@ -9295,7 +9632,7 @@
        "    <g id=\"ytick_8\">\n",
        "     <g id=\"line2d_14\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m1b5f838c68\" y=\"141.030958\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"141.030958\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_15\">\n",
@@ -9310,7 +9647,7 @@
        "    <g id=\"ytick_9\">\n",
        "     <g id=\"line2d_15\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m1b5f838c68\" y=\"112.182153\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"112.182153\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_16\">\n",
@@ -9325,7 +9662,7 @@
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        "     <g id=\"line2d_16\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m1b5f838c68\" y=\"83.333348\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"83.333348\"/>\n",
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        "     <g id=\"text_17\">\n",
@@ -9340,7 +9677,7 @@
        "    <g id=\"ytick_11\">\n",
        "     <g id=\"line2d_17\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m1b5f838c68\" y=\"54.484543\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"54.484543\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_18\">\n",
@@ -9355,7 +9692,7 @@
        "    <g id=\"ytick_12\">\n",
        "     <g id=\"line2d_18\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m1b5f838c68\" y=\"25.635738\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"25.635738\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_19\">\n",
@@ -9439,15 +9776,15 @@
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p7035afc62c)\">\n",
-       "    <image height=\"148\" id=\"imageb9e67ad1b6\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"387.781618\" xlink:href=\"data:image/png;base64,\n",
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\" y=\"-22.024007\"/>\n",
+       "   <g clip-path=\"url(#p83e4e5e29f)\">\n",
+       "    <image height=\"148\" id=\"image9920c77a7e\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"387.781618\" xlink:href=\"data:image/png;base64,\n",
+       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y=\"-22.024007\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_5\">\n",
        "    <g id=\"xtick_7\">\n",
        "     <g id=\"line2d_19\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.925862\" xlink:href=\"#m9124cecd13\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.925862\" xlink:href=\"#m72ce32f50b\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_21\">\n",
@@ -9460,7 +9797,7 @@
        "    <g id=\"xtick_8\">\n",
        "     <g id=\"line2d_20\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"445.623472\" xlink:href=\"#m9124cecd13\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"445.623472\" xlink:href=\"#m72ce32f50b\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_22\">\n",
@@ -9475,7 +9812,7 @@
        "    <g id=\"xtick_9\">\n",
        "     <g id=\"line2d_21\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"503.321082\" xlink:href=\"#m9124cecd13\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"503.321082\" xlink:href=\"#m72ce32f50b\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_23\">\n",
@@ -9492,7 +9829,7 @@
        "    <g id=\"ytick_13\">\n",
        "     <g id=\"line2d_22\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m1b5f838c68\" y=\"169.879763\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5f1f9375ae\" y=\"169.879763\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_24\">\n",
@@ -9505,7 +9842,7 @@
        "    <g id=\"ytick_14\">\n",
        "     <g id=\"line2d_23\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m1b5f838c68\" y=\"141.030958\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5f1f9375ae\" y=\"141.030958\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_25\">\n",
@@ -9520,7 +9857,7 @@
        "    <g id=\"ytick_15\">\n",
        "     <g id=\"line2d_24\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m1b5f838c68\" y=\"112.182153\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5f1f9375ae\" y=\"112.182153\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_26\">\n",
@@ -9535,7 +9872,7 @@
        "    <g id=\"ytick_16\">\n",
        "     <g id=\"line2d_25\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m1b5f838c68\" y=\"83.333348\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5f1f9375ae\" y=\"83.333348\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_27\">\n",
@@ -9550,7 +9887,7 @@
        "    <g id=\"ytick_17\">\n",
        "     <g id=\"line2d_26\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m1b5f838c68\" y=\"54.484543\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5f1f9375ae\" y=\"54.484543\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_28\">\n",
@@ -9565,7 +9902,7 @@
        "    <g id=\"ytick_18\">\n",
        "     <g id=\"line2d_27\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m1b5f838c68\" y=\"25.635738\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"387.781618\" xlink:href=\"#m5f1f9375ae\" y=\"25.635738\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_29\">\n",
@@ -9615,15 +9952,15 @@
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p9dfafd6553)\">\n",
-       "    <image height=\"148\" id=\"imagea31cb6981f\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
-       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\" y=\"-199.929462\"/>\n",
+       "   <g clip-path=\"url(#p4b977603e9)\">\n",
+       "    <image height=\"148\" id=\"imagebc107f697d\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
+       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y=\"-199.929462\"/>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.431744\" xlink:href=\"#m72ce32f50b\" y=\"347.929462\"/>\n",
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@@ -9636,7 +9973,7 @@
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@@ -9651,7 +9988,7 @@
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"148.826965\" xlink:href=\"#m72ce32f50b\" y=\"347.929462\"/>\n",
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@@ -9668,7 +10005,7 @@
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@@ -9741,7 +10078,7 @@
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@@ -9818,15 +10155,15 @@
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-       "    <image height=\"148\" id=\"image27059af5ef\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"210.534559\" xlink:href=\"data:image/png;base64,\n",
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\" y=\"-199.929462\"/>\n",
+       "   <g clip-path=\"url(#pd6cb91271d)\">\n",
+       "    <image height=\"148\" id=\"image820e81b7e8\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"210.534559\" xlink:href=\"data:image/png;base64,\n",
+       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y=\"-199.929462\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_9\">\n",
        "    <g id=\"xtick_13\">\n",
        "     <g id=\"line2d_37\">\n",
        "      <g>\n",
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@@ -9839,7 +10176,7 @@
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@@ -9854,7 +10191,7 @@
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"347.785218\"/>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"290.087608\"/>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"261.238802\"/>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"232.389997\"/>\n",
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@@ -9944,7 +10281,7 @@
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        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"203.541192\"/>\n",
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        "     </g>\n",
        "     <g id=\"text_49\">\n",
@@ -10015,7 +10352,7 @@
        "    <g id=\"xtick_16\">\n",
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        "      <g>\n",
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        "      <g>\n",
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        "      <g>\n",
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        "      <g>\n",
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        "   </g>\n",
        "   <g id=\"matplotlib.axis_3\">\n",
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_12\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"226.264943\" xlink:href=\"#m1502e261cf\" y=\"204.936307\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"226.264943\" xlink:href=\"#mce3ac5229e\" y=\"204.936307\"/>\n",
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        "     <g id=\"text_15\">\n",
@@ -10797,7 +11134,7 @@
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        "     <g id=\"line2d_13\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"256.701307\" xlink:href=\"#m1502e261cf\" y=\"204.936307\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"256.701307\" xlink:href=\"#mce3ac5229e\" y=\"204.936307\"/>\n",
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@@ -10810,7 +11147,7 @@
        "    <g id=\"xtick_8\">\n",
        "     <g id=\"line2d_14\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"287.13767\" xlink:href=\"#m1502e261cf\" y=\"204.936307\"/>\n",
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@@ -10824,7 +11161,7 @@
        "    <g id=\"xtick_9\">\n",
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        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"317.574034\" xlink:href=\"#m1502e261cf\" y=\"204.936307\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"317.574034\" xlink:href=\"#mce3ac5229e\" y=\"204.936307\"/>\n",
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        "     </g>\n",
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@@ -10838,7 +11175,7 @@
        "    <g id=\"xtick_10\">\n",
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-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"348.010398\" xlink:href=\"#m1502e261cf\" y=\"204.936307\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"348.010398\" xlink:href=\"#mce3ac5229e\" y=\"204.936307\"/>\n",
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        "     <g id=\"text_19\">\n",
@@ -10860,7 +11197,7 @@
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@@ -10873,7 +11210,7 @@
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        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#ma033c20fd0\" y=\"171.456307\"/>\n",
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@@ -10886,7 +11223,7 @@
        "    <g id=\"ytick_9\">\n",
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        "      <g>\n",
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@@ -10914,7 +11251,7 @@
        "    <g id=\"ytick_11\">\n",
        "     <g id=\"line2d_21\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#ma033c20fd0\" y=\"80.147216\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m83c753ef4d\" y=\"80.147216\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_25\">\n",
@@ -10928,7 +11265,7 @@
        "    <g id=\"ytick_12\">\n",
        "     <g id=\"line2d_22\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#ma033c20fd0\" y=\"49.710852\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m83c753ef4d\" y=\"49.710852\"/>\n",
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        "     <g id=\"text_26\">\n",
@@ -11019,10 +11356,10 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
-       "  <clipPath id=\"pb37736bdcd\">\n",
+       "  <clipPath id=\"p8091e3bb3f\">\n",
        "   <rect height=\"182.618182\" width=\"152.181818\" x=\"40.603125\" y=\"22.318125\"/>\n",
        "  </clipPath>\n",
-       "  <clipPath id=\"p437b873549\">\n",
+       "  <clipPath id=\"p69fff7663d\">\n",
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        " </defs>\n",
@@ -11040,7 +11377,7 @@
    ],
    "source": [
     "R_mis_ind = 10\n",
-    "u.plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map[R_mis_ind],ex_map[R_mis_ind],\n",
+    "plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map[R_mis_ind],ex_map[R_mis_ind],\n",
     "                       kappa_radial[R_mis_ind],gammat_radial[R_mis_ind],r_bins)"
    ]
   },
@@ -11054,7 +11391,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 23,
    "id": "7e458c10",
    "metadata": {},
    "outputs": [
@@ -11069,7 +11406,7 @@
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        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2022-11-09T16:11:40.345236</dc:date>\n",
+       "    <dc:date>2022-11-10T14:27:07.619307</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -11106,10 +11443,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
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        "      <g>\n",
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@@ -11174,7 +11511,7 @@
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        "      <g>\n",
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@@ -11213,7 +11550,7 @@
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@@ -11294,7 +11631,7 @@
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        "     <g id=\"text_7\">\n",
-       "      <!-- 0.54 -->\n",
-       "      <g transform=\"translate(7.2 216.502732)scale(0.1 -0.1)\">\n",
+       "      <!-- 0.58 -->\n",
+       "      <g transform=\"translate(7.2 211.046266)scale(0.1 -0.1)\">\n",
        "       <defs>\n",
        "        <path d=\"M 684 794 \n",
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        "    </g>\n",
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"36.465625\" xlink:href=\"#mff676c5544\" y=\"181.817121\"/>\n",
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@@ -12625,7 +12966,7 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
-       "  <clipPath id=\"p6aee157f7e\">\n",
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From 2a696808205db42edcfda6c50a68639a186f4db4 Mon Sep 17 00:00:00 2001
From: Chris Davies <cdavies@cosmogw.kosmo.physik.uni-muenchen.de>
Date: Fri, 11 Nov 2022 12:26:06 +0100
Subject: [PATCH 07/14] updated new function string descriptions from modelling
 to be consistent with the rest of utils.py functions

---
 clmm/utils.py | 182 ++++++++++++++++++++++++++++++++++++++++++--------
 1 file changed, 154 insertions(+), 28 deletions(-)

diff --git a/clmm/utils.py b/clmm/utils.py
index da0579d69..5df9df822 100644
--- a/clmm/utils.py
+++ b/clmm/utils.py
@@ -12,10 +12,27 @@
 from astropy.cosmology import LambdaCDM #update
 
 class profiles:
-    '''A class to generate 2D covnergence profiles on a regular grid
-    ''' 
+    """A class to generate 2D covnergence profiles on a regular grid
+    """
+
     def __init__(self,M,c,z_l,z_s,sig=False):
         
+        """Initialise the halo and lensing geometry
+
+           Parameters
+           ----------
+           M: float
+               halo mass
+           c: float
+               halo concentration
+           z_l: float
+               lens redshift
+           z_s: flaot
+               source redshift
+           delta_sig: bool (optional)  
+               If False, return convergence profile, if True, return delta Sigma profile
+        """
+        
         self.M = M
         self.c = c
         self.z_l = z_l
@@ -28,6 +45,21 @@ def __init__(self,M,c,z_l,z_s,sig=False):
     
     def cosmology(self, H_0 = 70., Omega_m = 0.3, Omega_Lambda = 0.7, Tcmb0=2.725):
         
+        """ Set the cosmology of the object
+
+        Parameters
+        ----------
+        H_0: float
+            Hubble parameter
+        Omega_m: float
+            Mass density parameter (baryon + dark matter)
+        Omega_Lambda: float
+            Effective mass density of dark energy
+        Tcmb0: float
+            cmb temperature at z=0
+    
+        """
+
         self.H_0 = H_0
         self.Omega_m = Omega_m
         self.Tcmb0 = Tcmb0
@@ -37,12 +69,24 @@ def cosmology(self, H_0 = 70., Omega_m = 0.3, Omega_Lambda = 0.7, Tcmb0=2.725):
         
         
     def get_r_vals(self,nbins,lower_r,upper_r,log=False):
-        '''create radial bins for profiles
-        nbins: number of bins
-        lower_r: lowest bin value
-        upper_r: highest bin value
-        returns bin edges in units provided, or kpc if none are provided
-        '''
+        """Create radial bins for profiles
+        
+        Parameters
+        ----------
+        nbins: int
+            number of bins
+        lower_r: float
+            lowest bin value
+        upper_r: float
+            highest bin value
+        log: bool (optional)
+            return bins with linear (False) or log (True) separation
+
+        Returns 
+        -------
+        r_vals: np.ndarray    
+            bin edges in units provided, or kpc if none are provided
+        """
         #create r values
         self.nbins = nbins
         self.lower_r = lower_r
@@ -68,13 +112,18 @@ def get_r_vals(self,nbins,lower_r,upper_r,log=False):
         return self.r_vals
     
     def kappa_NFW(self,r_vals=None):
-        '''r_vals: radial bin values for halo lensing profile
-           M: halo mass
-           c: concentration
-           z_l: lens redshift
-           z_s: source redshift
-           delta_sig: If False, return convergence profile, if True, return delta Sigma profile
-        '''
+        """Produce a 1D NFW lensing profile
+
+        Parameters
+        ----------
+        r_vals: np.ndarray (optional) 
+           radial bin values for halo lensing profile
+        
+        Returns
+        -------
+        nfw: np.ndarray
+            1D NFW lensing profile
+        """
         
         if np.all(r_vals.value) == None:
             r_vals = self.r_vals
@@ -114,10 +163,20 @@ def kappa_NFW(self,r_vals=None):
             return (nfw.real / Sigma_crit).decompose()
 
     def make_grid(self,npix,r_max):
-        '''make 2D grid centered on origin
-        npix: resolution of grid
-        r_max: width of grid is 2*r_max
-        '''
+        """make 2D grid centered on origin
+        
+        Parameters
+        ----------
+        npix: int 
+            resolution of grid
+        r_max: float 
+            width of grid is 2*r_max
+
+        Returns
+        -------
+        r_2D: np.ndarray
+            2D grid centered on origin
+        """
         
         npix *= 1j #imaginary so that ogrid knows to interpret npix as array size
         y,x = np.ogrid[-r_max:r_max:npix,-r_max:r_max:npix]
@@ -126,9 +185,20 @@ def make_grid(self,npix,r_max):
         return r_2D
 
     def kappa_NFW_2D(self,npix,r_max):
+        """Create 2D NFW profile on grid
         
-        '''create 2D NFW profile on grid
-        '''
+        Parameters
+        ----------
+        npix: int
+            resolution of grid
+        r_max: float
+            set width of grid (2*r_max)
+
+        Returns
+        -------
+        kappa_NFW: np.ndarray
+            2D NFW map
+        """
         
         self.npix = npix
         self.r_max = r_max
@@ -139,9 +209,21 @@ def kappa_NFW_2D(self,npix,r_max):
 
 
 def KaiserSquires(Sigma):
-    '''Apply the Kaiser Squires algorithm to a 2D convergence field
-       Returns the complex shear as e1 and e2
-    '''
+    """Apply the Kaiser Squires algorithm to a 2D convergence field
+
+       Parameters
+       ----------
+       Sigma: np.ndarray
+           convergence map       
+
+       Returns 
+       -------
+       e1: np.ndarray
+           real component of complex shear map
+       e2: np.ndarray
+           imaginary component of complex shear map
+    """
+    
     kappa_tilde = np.fft.fft2(Sigma)
 
     k = np.fft.fftfreq(kappa_tilde.shape[0])
@@ -161,9 +243,30 @@ def KaiserSquires(Sigma):
     return e1, e2
 
 def getTangetial(e1, e2, center, dx=10./1000.):
-    '''Measure the tangential and cross shear maps from the e1 and e2 maps
+    """Measure the tangential and cross shear maps from the e1 and e2 maps
        Requires a center as an input, about which the tangential and cross maps are calculated
-    '''
+
+       Parameters
+       ----------
+       e1: np.ndarray
+           real component of complex shear map
+       e2: np.ndarray
+           imaginary component of complex shear map
+       center: list
+           x and y coordinates of the center of the map as numpy array indices [center 1, center 2]
+      
+       Returns
+       -------
+       et: np.ndarray
+           tangentail shear map
+       ex: np.ndarray
+           cross shear map
+       radius: np.ndarray
+           radius map
+       anlge: np.ndarray
+           angle map       
+    """
+
     n = e1.shape[0]
 
     xx = np.arange(-n/2, n/2)*dx
@@ -186,8 +289,31 @@ def getTangetial(e1, e2, center, dx=10./1000.):
     return et, ex, radius, angle
 
 def getRadial(radius_map,r_bins,angle_map,phi_bins,kappa_map,et_map):
-    '''Bin a map into radial and angular bins as a 2d histogram
-    '''
+    """Bin a map into radial and angular bins as a 2d histogram
+    
+    Parameters
+    ----------
+    radius_map: np.ndarray
+        2d radius map
+    r_bins: np.ndarray
+        1d radial bins
+    angle_map: np.ndarray
+       2d angle map
+    phi_bins: np.ndarray
+       1d angular bins
+    kappa_map: np.ndarray
+       2d convergence map
+    et_map: np.ndarray
+       2d tangential shear map
+            
+    Returns
+    -------
+    kappa_radial: np.ndarray
+        1d convergence radial profile
+    gammat_radial: np.ndarray
+        1d tangential shear radial profile
+
+    """
     _N = np.zeros((len(r_bins)-1, len(phi_bins)-1))
     _K = np.zeros((len(r_bins)-1, len(phi_bins)-1))
     _GT = np.zeros((len(r_bins)-1, len(phi_bins)-1))

From 5e843fad9a0b953af3bf337e255201f9ff068082 Mon Sep 17 00:00:00 2001
From: Chris Davies <cdavies@cosmogw.kosmo.physik.uni-muenchen.de>
Date: Fri, 24 Feb 2023 15:03:18 +0100
Subject: [PATCH 08/14] removed bug leading to strange tangential shear
 profiles

---
 clmm/utils.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/clmm/utils.py b/clmm/utils.py
index 5df9df822..809b1e390 100644
--- a/clmm/utils.py
+++ b/clmm/utils.py
@@ -11,6 +11,9 @@
 
 from astropy.cosmology import LambdaCDM #update
 
+def hello_world():
+    print('hello world')
+
 class profiles:
     """A class to generate 2D covnergence profiles on a regular grid
     """
@@ -139,7 +142,7 @@ def kappa_NFW(self,r_vals=None):
         delta_c = (200./3.) * ( self.c**3 / ( np.log(1+self.c) - ( self.c/(1+self.c) ) ) )
         
         x = r_vals/r_s
-        x = x.value
+        print(x)
 
         Sigma_crit_coeff = c**2 / (4. * np.pi * G)
 

From 22eff54d78816bb858d6a0458c642d929d030c58 Mon Sep 17 00:00:00 2001
From: Chris Davies <cdavies@cosmogw.kosmo.physik.uni-muenchen.de>
Date: Fri, 24 Feb 2023 16:24:13 +0100
Subject: [PATCH 09/14] removed spurious test function

---
 clmm/utils.py | 3 ---
 1 file changed, 3 deletions(-)

diff --git a/clmm/utils.py b/clmm/utils.py
index 809b1e390..1b06129d2 100644
--- a/clmm/utils.py
+++ b/clmm/utils.py
@@ -11,8 +11,6 @@
 
 from astropy.cosmology import LambdaCDM #update
 
-def hello_world():
-    print('hello world')
 
 class profiles:
     """A class to generate 2D covnergence profiles on a regular grid
@@ -142,7 +140,6 @@ def kappa_NFW(self,r_vals=None):
         delta_c = (200./3.) * ( self.c**3 / ( np.log(1+self.c) - ( self.c/(1+self.c) ) ) )
         
         x = r_vals/r_s
-        print(x)
 
         Sigma_crit_coeff = c**2 / (4. * np.pi * G)
 

From ff4383af9cc793a9d6decb75e22e2c61f93c7326 Mon Sep 17 00:00:00 2001
From: Chris Davies <cdavies@cosmogw.kosmo.physik.uni-muenchen.de>
Date: Fri, 24 Feb 2023 16:24:45 +0100
Subject: [PATCH 10/14] fixed bug leading to incorrect lensing maps and
 tangential shear profiles

---
 examples/demo_modelling.ipynb | 5636 ++++++++++++++-------------------
 1 file changed, 2346 insertions(+), 3290 deletions(-)

diff --git a/examples/demo_modelling.ipynb b/examples/demo_modelling.ipynb
index cf4b70c94..364a1f502 100644
--- a/examples/demo_modelling.ipynb
+++ b/examples/demo_modelling.ipynb
@@ -19,7 +19,8 @@
     "from clmm.galaxycluster import GalaxyCluster\n",
     "import matplotlib.pyplot as plt\n",
     "\n",
-    "import clmm.utils as u"
+    "import clmm.utils as u\n",
+    "from clmm.constants import Constants as const"
    ]
   },
   {
@@ -62,46 +63,38 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "8aea13a2",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#Define the center of the map (in Mpc)\n",
-    "center_1 = 0\n",
-    "center_2 = 0\n",
-    "\n",
-    "#define radial and angular bins\n",
-    "N_r_bins = 30\n",
-    "N_phi_bins = 25\n",
-    "r_bins = np.insert(np.logspace(-2, 1, N_r_bins), 0, 0)\n",
-    "phi_bins = np.linspace(-np.pi, np.pi+0.01, num=N_phi_bins+1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
    "id": "909edd57",
    "metadata": {},
    "outputs": [],
    "source": [
-    "from astropy import constants as const #update\n",
     "from astropy import units as un\n",
     "\n",
     "#specify parameters for NFW halo\n",
-    "c = 1 #concentration\n",
-    "z_l = 1.0 #lens redshift\n",
-    "z_s = 2.0 #source redshift\n",
-    "Mass = 1E13 * const.M_sun\n",
+    "c = 10 #concentration\n",
+    "z_l = 0.5 #lens redshift\n",
+    "z_s = 1.0 #source redshift\n",
+    "Mass = 1E14 * const.SOLAR_MASS.value * un.kg\n",
     "\n",
     "#define physical size of grid\n",
-    "units = un.mpc\n",
-    "r_max = 10 * units\n",
+    "units = un.Mpc\n",
+    "r_min = 0 * units\n",
+    "r_max = 50 * units\n",
     "\n",
     "#number of pixels in grid\n",
     "npix = 512\n",
     "\n",
     "#define physcial size of a pixel\n",
-    "dx = r_max/npix"
+    "dx = r_max/npix\n",
+    "\n",
+    "#Define the center of the map (in Mpc)\n",
+    "center_1 = 0\n",
+    "center_2 = 0\n",
+    "\n",
+    "#define radial and angular bins\n",
+    "N_r_bins = 30\n",
+    "N_phi_bins = 25\n",
+    "r_bins = np.insert(np.logspace(-2, np.log10(r_max.value), N_r_bins), 0, r_min.value) * units\n",
+    "phi_bins = np.linspace(-np.pi, np.pi+0.01, num=N_phi_bins+1)"
    ]
   },
   {
@@ -114,20 +107,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "id": "5b51bbc8",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: function 'sqrt' is not known to astropy's Quantity. Will run it anyway, hoping it will treat ndarray subclasses correctly. Please raise an issue at https://github.com/astropy/astropy/issues.  [astropy.units.quantity]\n"
+     ]
+    }
+   ],
    "source": [
     "#lensing_map has the option to return either Sigma map or the convergence map.\n",
     "lensing_map = u.profiles(Mass, c, z_l, z_s, sig=False) \n",
     "#make map\n",
-    "kappa_map = lensing_map.kappa_NFW_2D(npix,r_max)"
+    "kappa_map = lensing_map.kappa_NFW_2D(npix,r_max) "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "id": "b0dc4b6c",
    "metadata": {},
    "outputs": [
@@ -137,12 +138,12 @@
        "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n",
        "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
        "  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
-       "<svg height=\"265.995469pt\" version=\"1.1\" viewBox=\"0 0 343.812937 265.995469\" width=\"343.812937pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
+       "<svg height=\"265.995469pt\" version=\"1.1\" viewBox=\"0 0 340.634812 265.995469\" width=\"340.634812pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
        " <metadata>\n",
        "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2022-11-10T14:23:26.732168</dc:date>\n",
+       "    <dc:date>2023-02-24T16:18:02.711480</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -158,24 +159,24 @@
        " <g id=\"figure_1\">\n",
        "  <g id=\"patch_1\">\n",
        "   <path d=\"M 0 265.995469 \n",
-       "L 343.812937 265.995469 \n",
-       "L 343.812937 0 \n",
+       "L 340.634812 265.995469 \n",
+       "L 340.634812 0 \n",
        "L 0 0 \n",
        "z\n",
        "\" style=\"fill:none;\"/>\n",
        "  </g>\n",
        "  <g id=\"axes_1\">\n",
        "   <g id=\"patch_2\">\n",
-       "    <path d=\"M 48.982812 228.439219 \n",
-       "L 266.422812 228.439219 \n",
-       "L 266.422812 10.999219 \n",
-       "L 48.982812 10.999219 \n",
+       "    <path d=\"M 55.345312 228.439219 \n",
+       "L 272.785312 228.439219 \n",
+       "L 272.785312 10.999219 \n",
+       "L 55.345312 10.999219 \n",
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#peee7dd125c)\">\n",
-       "    <image height=\"218\" id=\"imaged815d3a7c1\" transform=\"scale(1 -1)translate(0 -218)\" width=\"218\" x=\"48.982812\" xlink:href=\"data:image/png;base64,\n",
-       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\" y=\"-10.439219\"/>\n",
+       "   <g clip-path=\"url(#p905262e581)\">\n",
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+       "  <clipPath id=\"p905262e581\">\n",
+       "   <rect height=\"217.44\" width=\"217.44\" x=\"55.345312\" y=\"10.999219\"/>\n",
        "  </clipPath>\n",
-       "  <clipPath id=\"pa5644586ad\">\n",
-       "   <rect height=\"217.44\" width=\"10.872\" x=\"283.162813\" y=\"10.999219\"/>\n",
+       "  <clipPath id=\"pc624a02830\">\n",
+       "   <rect height=\"217.44\" width=\"10.872\" x=\"289.525313\" y=\"10.999219\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
        "</svg>\n"
@@ -967,7 +902,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "id": "2aaf9cb0",
    "metadata": {},
    "outputs": [],
@@ -980,7 +915,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "id": "72993065",
    "metadata": {},
    "outputs": [
@@ -990,12 +925,12 @@
        "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n",
        "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
        "  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
-       "<svg height=\"265.995469pt\" version=\"1.1\" viewBox=\"0 0 352.062937 265.995469\" width=\"352.062937pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
+       "<svg height=\"272.794688pt\" version=\"1.1\" viewBox=\"0 0 336.159812 272.794688\" width=\"336.159812pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
        " <metadata>\n",
        "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2022-11-10T14:23:27.062237</dc:date>\n",
+       "    <dc:date>2023-02-24T16:18:03.115009</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -1010,25 +945,25 @@
        " </defs>\n",
        " <g id=\"figure_1\">\n",
        "  <g id=\"patch_1\">\n",
-       "   <path d=\"M 0 265.995469 \n",
-       "L 352.062937 265.995469 \n",
-       "L 352.062937 0 \n",
+       "   <path d=\"M 0 272.794688 \n",
+       "L 336.159812 272.794688 \n",
+       "L 336.159812 0 \n",
        "L 0 0 \n",
        "z\n",
        "\" style=\"fill:none;\"/>\n",
        "  </g>\n",
        "  <g id=\"axes_1\">\n",
        "   <g id=\"patch_2\">\n",
-       "    <path d=\"M 48.982812 228.439219 \n",
-       "L 266.422812 228.439219 \n",
-       "L 266.422812 10.999219 \n",
-       "L 48.982812 10.999219 \n",
+       "    <path d=\"M 55.345312 235.238438 \n",
+       "L 272.785312 235.238438 \n",
+       "L 272.785312 17.798438 \n",
+       "L 55.345312 17.798438 \n",
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p49e3b0aac0)\">\n",
-       "    <image height=\"218\" id=\"image345bc000be\" transform=\"scale(1 -1)translate(0 -218)\" width=\"218\" x=\"48.982812\" xlink:href=\"data:image/png;base64,\n",
-       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\" y=\"-10.439219\"/>\n",
+       "   <g clip-path=\"url(#pefad40b9cd)\">\n",
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    "source": [
     "axlim = 2*r_max.value\n",
-    "plt.imshow(kappa_map,extent=[-axlim,axlim,-axlim,axlim],origin='lower')\n",
+    "plt.imshow(Sigma_map,extent=[-axlim,axlim,-axlim,axlim],origin='lower')\n",
     "plt.xlabel('x ({0})'.format(r_max.unit))\n",
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-   "execution_count": 9,
+   "execution_count": 8,
    "id": "eec34ea3",
    "metadata": {},
    "outputs": [
@@ -1975,10 +1928,10 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:149: RuntimeWarning: divide by zero encountered in true_divide\n",
-      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:149: RuntimeWarning: invalid value encountered in multiply\n",
-      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:150: RuntimeWarning: divide by zero encountered in true_divide\n",
-      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:150: RuntimeWarning: invalid value encountered in multiply\n"
+      "/home/cdavies/miniconda3/envs/clmm/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:231: RuntimeWarning: divide by zero encountered in true_divide\n",
+      "/home/cdavies/miniconda3/envs/clmm/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:231: RuntimeWarning: invalid value encountered in multiply\n",
+      "/home/cdavies/miniconda3/envs/clmm/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:232: RuntimeWarning: divide by zero encountered in true_divide\n",
+      "/home/cdavies/miniconda3/envs/clmm/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:232: RuntimeWarning: invalid value encountered in multiply\n"
      ]
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   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "id": "2ba6da86",
    "metadata": {},
    "outputs": [
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\" y=\"-10.226875\"/>\n",
+       "   <g clip-path=\"url(#pe76643739d)\">\n",
+       "    <image height=\"218\" id=\"image2d1f2357b1\" transform=\"scale(1 -1)translate(0 -218)\" width=\"218\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
+       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@@ -2414,7 +2367,7 @@
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        "   </g>\n",
        "   <g id=\"patch_8\">\n",
-       "    <path clip-path=\"url(#p70000390b5)\" d=\"M 267.4675 228.226875 \n",
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RRg9ZBNiW+cgpAksvGyKMJhUDnAnxY1S3W2CDA4xVzQPHKtb7UN6W9huseaN1q0yfnKqZXn4LZDVYD3667puOk7vVlOHz55RMJMoB1/0yebdWqVj/RW7bqDX1kL87flM9n+ee2vYA3LRTkVHNxl4fDNUMspOa94B5uKyixT6a7uXP/llGtcqGFEDnu9iYJUbd9mCDV1GnalHQY1QxdaNEPUfUpTjeBWuSjLpFEMi8u5sOQjaAtQNYDNzBg5GHXNCWRvszwAHtqtENXnMaVEwfa2Q2mgfmUG8Hm08eMj2toIt6f2i/TEcXRb2ggFOQRYB1RWtgRT3yZ2lJK1a56VVgRE5MbFIiMCf3YNMpJ0xVjd/M1up2SMUi4Ci96Gsy0183valmmOR7yCJF0yZiAPr0fbV5EKwV5Yeley3Gm4wauN5QDYB8saQenTWruvFymq8MGy/XD9Ho3M6SPO34BoExG9t8VzOOMOq8E/lo7JN5yE55DQHzcNmo43blvYK17TTwBDoFnFv7MGxGvTBXNdlVckGRfjsEaoZD12jzNZnoPBkFm5Qf1a2OQDiQ+jb2IYtUTtZVdTJgHTgZFPySi9QgUWeZ7t5+fisS+WdyzT1sDJQzIWfqZlXs4FUEzMXiULU2G3k+Mhl94EPnn9JqVEwD5uHyyraXtIJp07HDUyxwE9jYzFS5Rll0G530IGGYlarxeRtUzJmIocLpSxVctsPBkF1r4DXqNoFuLFcnvloHTK6x2VescOPOepmaUgNPQ4feLtZsLUC8M/2AdVFG9te0CcmqJeqG2HyUOh/x0fiEzcxGYDAZl2R9Mp4+pWJMxZNMdwXbMxu3+jl6BWvboLA+Q6eAA6J8Wkaw6ZRRQxNydeqmVW31KsY+2STtLdfptAfQ1vJj6harmSQDW3Xz+reGUMo6DrCwS9bRh0UKzEeGLrd87vUhN3V2sNXaopHokPXjJ9u/wgRFBCh9jtw5ldnIP2PIOCt1v8yrmQ6KMEg2ukjAkcppFdszG48omkQR4Rupe8cpC5bqyTg8eEYz0puQAhEsVKxq8oY1n8pk/bP+G8B1wPAIFW0KV5TvYdPldtQtmbzbIBtUbAZYVD9gPFtRwzVdKOmGxXABrddHVo3WxcHGV5rNxAiqCVD6PG1dv9mnmbSfxr+6s7BvKzOmozIXPWTnVIyCMXQ8335tjRdY6FbVJ0QCGwDGaOIMrBLkUX4Amw50aFXj+VUt92bha+HSZW8LhujpyU4Gdasub6JmUd4mZAxQUXluH32/fQfzh0hfoNvPNHSJFKMmBq6yPSYN0xq2CCqtahpCgRG9jDxd3bNjloaBdJx6zdSswzRCdsrroGJ93sLFUG02VMP2AllSg2/eQO3eN0oubwJb72XSVT5SNe6atVabF0UZh4AIgK1Io06vC+8HUPG+2+/kBnfwDaF8Lr8BmTYVTdOB2Xa1+y5HDoquS26PMd9orYFDTagLwI3WBrYKfqRC3w2ilJM/c914/kiFlV/WTMjRbNRqdsoFSy44JfpV6hVBZoHrQHm49iKNnEwbWaWLmdQbZUbhlJdVXZ6DjS+xBEDQDIuCrmLFqRhPa/Nx8NOOALWhcsd7hngIZst3lqVomrcZKZxZtgHZDDAFV2je+sTncq09nJ/5rKMDBwJspUKLgw1Joo5Gvdivq7Dhfa6T/ntJkqAHzcr82Fvft5ud8jpAxkERDRkD5uHSZuIMONOelZSPVpMDjqZ7hEn6P3rYbL9Ja0KaN7IBajqwjeOrA2iz3UwDd1DNgN0XP/c3MjfF3PIJqFFDtlez2fYHyALA4v1v3MW0yDRaM3QeuAQk7qG/wsA2Mw2tevWgCNxp6OUOOAOkYNyO5s1HA5T+g54vBjgPGZuUHjCvaMtOIGRJwCohfeWjpWyAY5PShXNNT39O2jxsqaDURerlfTUfadT+mXn3Mt3QYL0D3U19HQcFmi13v5GSDBDtKJxRswlk2kT0dZm/GNozqgqIhI3WtQPHYf1a6IJkBVtNgdlYIT6fVjIDHkbgoMr4pM1FvyhZH03emFbQscl4Siv9lgGyswrzM2QeOIbLh/M1dGt1QRA5L2wSevOR8tIIm+slYOa9bxbNa0VjuHLCrp8WBUqOpmPfR9tJB83yUF1Cc9K1e70IsglgRs3cwzfpinFjc0oGOtNVIAOtsTpJD/3W6F27n6b/SpVAivh+pHy+7yNPHzy1XcnoT/o3wipbbz8rgarVELKzarRmwDxcM9jkdBq4gO6DqegiIHDJeCAHYdMK1lLL0yYjL2fz0ZuM8Xk9ombYvVAv6r0vaaZUCBQkULdZsMSoGeftQaZNxWr3L9Omp8jOmVkBJBqaRUMnWgbUUps5Kb1BekO1+Gl0N0jkkgGiB0eU781smdVVTvE0+2c+CLKYHvsqypi7mp3zKn7YHmQZc9hmaYEyGwk8ydPACVx83HPYjA8WqBrD7QMfqP3zvF7FIm50iP+WhmpONCT4cQm8JYUKBptn1QdTNQu3rZUMDjINvARPFIymLi6DTUgyFQfoJMpHZ3yxsAEtGtnVrHfVElVj2DRc/sG1df6krurgNXCD6TiqmXSvIrjYP/OQ8a8GbFAyBdniKryqiuWk/CytakbhGmzc5sbKVrAMh9/9s1HVWgCYp5MBr9fH+mnm1L4AqFk6pGjjjTmZ3spT+TMTUk/vqZlJpQ6QGRXzgO11yZJHFyS0L9CV1AMgrG5rDJs8YnlSm4xGzdpFrlzHmYrNUggYjIIlwPVhLEbVzuSfbUF2ps6gAhv3DKFKTl+LAWwQw5fTiqbfLVJmZNs+n7htVevvtln4dMTRNC/oU7kDnFe7ozC+znT0aaY8mMDlyozTgZqJmdVNxj3IBsC02u0cT1U+WSJuuH3F+GhrV5TWQ7/SC6Htl8ed4Dr3AItTtJmSRVV15mMfibhlsdmoFU18M1G10t9DS1UgO+WCBd2cNGqWygCXVzGflrR2ZRv8s5ZXkJpCBrC1Mt2EZIAAHejoxx2Zj1Le+WkxXC97wXNItG31IcJXbOwWVZP917HcTGnqBLqjkM0Acw3YDKRp6lGBjRaVrBa4Bb1tTBqqu+Kxfyb9IpWqVal7NyNZzbRvloJDVxUcDmDLbNRqxkEP9s9Oae0K5iBr+RawmZJxyF93t2on1gEWzG/BZtrLQpPRhfV1B+IJUDpx5PFLpBc1WIfze/k7aapqPjKo1WyWPGQTwMw2osAMS4M0XjfoBDgk1LUpSF3YZASNS61AKiSBG/4Zt6lpRZPle4mA4ip7yMSERG8z436NEr5HB/GcVoHsnFajYvoX2G6kNu1kQH8oRMA52KKko5D6GRlB1acPnL+NNHvbWo7n4Pbf1nScpYn5eMRXM9N6fqZmW5CZyKRWz8nZUmEm9tVqqQo4stEzkFYHW1uRKtgkrIX223wLxac+qKpTtiE+o/IqB2Nc6qH8LrAMm+5yxb0/znkV2Jp/toaQaTXTgEU9QnzqDc8KPAXcioRsFAx9etNfK7J+23Y105G5qAMiPvLoyx4J/e8mBeJvA9rBNPhnwfRMzY5AZny1jfa0MVXwS5uJGqhaaJ90rVQDGyqQSAVRVRsbmY8GKr6fdJUG6NQV88fOPllSkLGSse/leuFzAKTDVkLIzvk6qJiE+Omk7YX0hzonggagG3EbNu2LAWMEclGqpad70GPcxu+RvixoL5XtiaoNgCk1myUDmUgCm5CqjGzTSwmbj+Sj5dqBq1Qp+XCY2gwHSEAwrq1s1eB5c7EqP+3Gc9cDIWxCdrNRQ8dtZgvBpv0yDvVryLqajYBl9YTy44Ssgcm41tzWN8ENGGXyqfliTdW0/5QNVLGfdkt6MxWbpN9P0Q7cSOZhGZmNOgVqNoXMA+Z/TT2rwCZheAYOoG5Yle8X51Mq07FUYO2fdWJ1S8o6EvDM/g8EQ9zJ0D6avGNGXa3ER0v9/bJTVoq2AxkDpsGKTEdtMhoFo2Nqr8ZUAxsCVVv1NjGaj1Hw488mqcvyu5uOxpybpSOqdiQRZFPAplZQhQ6gdeAA5KZuFf1+aaYjZ/QgCAdGeIAeH3UMp4NzMJwMFdbv75p1Jesh/aoA6+1lDBD7ZBoyvVwD1jsTb5iOXOcUAFeDqGSQOAKpgWvqQ9PKN/PJ+2VfWrW2UgdtL4JyQ4TlNWkzmjiUdU/yLTWLINsyIX1i09H7a/xOGjWqczIPZmnjQguAlFbZ5LttTYDbvS6y6QYbA8ZmY++V3zsIn3WjNAVCGLb2d+1h/nRtY4s4uPbazvoJ4Pnc2q9Q+v3EPlugaroj8nKDSfjF1C2wNo6mlyvaEfC2yrwE3K0eHVuRQ90NK8gbFM5vU5uOKVl/DRQESQAW9JG0qIoNgAR+4wOp0r3UgEsUCEmFlmvIYFVNnzI9jEEU2u89813wg9vMqI+jMRkdZHfpKirWzMfedqaDIOyrld12MwhsnNgcjNqvPFxayRbEXbK20hZ8X8zspO020Hz7wK1J3wE3AiRdkl6Thra2GvpxiQHzkEWgmTB97QEPgm0wH3NGXTHCxqF8hrESYAWoufWBTNQ5uVbrp+2bjmpS+WV+IB4DG6nbAur5kVSUMYDsToX2eydiHQTRfRytCsVhfBgV4/ILuqrpy9lMw9elWbvctLxi4U16h+Cgor0ahkPq1+Let+5rMPduXdcESbRiug3xo1TMR4IBQC0JQCFfLbdu6gVkJnY/KlHnZKRKKpbEp5OoYyGFO2w6VhMQSUAbHBXKbEw90mjULPfgB/tsDBn7ZhqyTL4asGE2mm5VTeW6n3Xsps2pYFVKdovZCHRQjqjUzUaVnz+4gZeZjjMF21G2N1GvrRSZfto3i+a5XKl2G1umaEoNvOYQOV+toA33AgBtmqOMSfcOWYm5wqoWwHXwXOmx9X1XqxObkHlt885MtH7ZaiCTXiEEmHS52mx4bAq1SlcqCxsCVWtlLEgL6uZeXpsipbLPWa1qr9/fPmivDIKEcNE2bwbvLd9b4MSQHQn1R4lC8wD5agFsSNmYkPwOW1OuRL/thKQAMlE4vV9uJjDmIwbTkRuqWc2ki1Xwx5Cd03VQsQVVANtspJZK6ldgAv/NJe1/HUlHIpY69a/PjIDdah4Ot8aBer8uvP8SNYvA9eDxfIYKk8dV4Jcxh6pF5UN1C8xF+rXdqcyGKFJIqsZhxZyQkKlfJMHGbWiptp5E3GDNqsbRSTIb2U/rAKoLG/pprZD3z2TEYVGyYjsNu/C+h6xFGjtguyYjuoqtNSOjCFyLqBiMqq2DipUQSOP3ucTgdHMxh/NmnQ3TcqZkr32+b4PmgiRHFEiX2YLLDxFwu7qN29yu2EZhZ0Ymb0ZGuyfTUQbikfdmigRGEgpZR7lFCVcMqtYG8CHz0ZuNWtlqcMDKL+umI8Q/k47Ded1Qs6uZ1pCdsRrAdkcgVlFGhq31cIwVQ3eZOpJujQx6oGJzcVymq2TB2wiS7NTtxYoWAWXz0hiomChXXMaP1aHWnVXqtaalhyzy+cyIxk15BLhS5ISnnFvxtbbm0hVNvui9td7/sUPm/bXemL9R58SH3l/uPGVuYKaII3TXqjic36KQDbK7tFqTkXqHcGJVGwBKTUEWkuctJYqSNge3AiejepFfuGEeeug0tCFsL4k2blynOWgeAjUfqtZs3QiUqVnZQDEgokMn+fTikMCYAR8D3lVI7Zt5qDZD/jSvv6angVsysBY6dOmT0CrDJmRpAKYcmI8MWO3zgMrjmQQLGZmL2nw8SYRxdb3zrYrduWkb1rcmo1G1asHgED3f+GIygjsI3wYe0KFZB5OQ8y1cA1AKOp5miKLbY8+cxGx6K1XgdMhkO+KLOaB03qB4aVx22E+LYFT5dv+3KVzS4AFzHw5QbXfVQJfW0vw3OQUNttbPsXYTMldSMEiDNasZKtclCWyyZ2dC8shXOurYI40U0ufIYl4dYCNkbD4yZN5kND4a5bOKadiicH5GmQYxrMKwQhFcDJtENG3+nn8WqZdXsSjiOAcMcf5GChXtxfBtQBaVmfppR81HXQ5VAR0ESG41K2eesIaQzcgCCHApdbjkVLQnei3oJmSpRtWwdNXS6rYZ5qcHlvbPZERh+uOxGmeRxggyDRvQ4dKQNahYbouB7WiK+h2uAo+DbTD9ts3GLf9stiwKhGx1Rrol7fpoBjpvTqq82Gebg4IBljcyHxkofi89qUrPpmcpCvsXFxDIuUPHof5SkKpCndrdZNzFUtub2VrV2DcjJRPoeCOTqkZvVC/cbpaVig2wXeXvTuZXo2ILqjIZXQVoVoA7YBoW44ON0wKNNIy8jdlYakJBQqlpMBsH2PQhyjKdZ49/mI7mEYFmFGfbF4uDILGCheYjwQhy5JFo1x7CF5qPHUp0Hy7w53aTh8yYkAq8nCGh/iU3MxJoZiPQOq+TCZlyFVXDkpQZmUZFg5rXiaOOdL4Weou6v/oyNlBrk/FOGqxdIzUBpuHyasYdd4+qmA6MaCDX6szBV5iNDFP7yzJdPYATs3ErKBIFR4yBtPPMPuadBqaq7DcF5dzvUHaS3+eTzFcZN61PV/qTWDZomalfcttSJ68PExUfr2/EBiii2PNqre1P5+vptU2ntbT8tTRTsbT5VGpTuUJ/K/tp3WeDjz5GSQVCTI8QbTJOTccrzlinkPH0GT1yCWAKou50PEsaygKrVFtmo/1rHZMZrpXy9bamKrdjNm76Z+GyzcOVZBVNW1MbZuKWTzYqWDcfRXSofFexbVWrSK3j7kTVwD5ZBsADlbLPpM1Hga0q9Uvu0eQSAySzGj6CLvey0sM/U6ZWtpJE0VpH5K5qadEmJJuPdCK9ugGQAAiU6YgW6esmY3E99K/2D6RqBNmdvODZoQL629PtFZc23cdOrEDdDsfzMq1ea01Ya27TyKRALYCysjqhl+H1eN+sWBq4mZpps5E/Cl+lLEw+X3L9C33qpVBwvBsAHuiCxdSMK/cy6HCh/2oFq9g2KQ/5agRdSrXDyN8xIzJTrtS7QpulDdRaAn/OAwiVb07iCFjLL7StdhP0sT2tL9fOS+sXWQuAklqn4rUi0ftsTdUIMn6/bUfR+jtocG9T2yDIfb7gIV9wl1Y8pIuYjmw2esj6C54EGZIBjpd5wPR8A4bhsKbhlpoJYAoYr2ZtGxO1eoWa6b+WNz/3o3k3TzFoB6DS+9IsfnFVoyEAWl3aWMHep5NHPalaLfSSpnzqVgdRkvTM1+N8gL7cqc+0UbPqgiI8vwI15dYdy12ldOXqJSIrycufQ1CkdjNyGnmU0H4V/0yPoz/v09hg05CdUxHAIvPPN1L7kaZWUhk9L9MuyLGnZqtSqLY89XJvqGaAgkyucf+t5KMM0G3CF2fvdMGCAyb+lXPql0Et86qm8ixQen4EqXV5UuF8JBqNjE02tGW1LasJMqQbQPXS0NF+5Ex6U1L3BAHm7Wq2EFAyBXFc5KUk4Epd93NFupYGW4vNj71DlLKJuqX+p9+o5vH0eTDU+3zFQ77gPl+oL+MVD/lZmY8xZDPHnR8tS7JDAnhV06q1IrVfgSlTfu4KhSSgepNRw6b9sUvNBiqBTEMXQKYBM2ajASpQs9myI/BBgSbQuORNu+iXAdoGj/woXx59G3BlWvNTQm3fRm0qUWr7gMRKY+CTwg0m5II+uKmopQVM9s/qRV2pUlUHADR/iwMdgFWzsLNelf3UlM1tmFIb3CcVMjkXrWgVae0RSJQkcEXXxoT0UyX/jAfesSrG5iIHPzRkZ+k83AbViVJ/s7mbiyu6MvD8CqVMSqFkGakZAySA1YxLXaYm47UuWGvCtSxG1a78K/kWLv0HAN43U1e5qxicOakua/tNbj4+Zzp/UDRhKALPQ6bLBcrlVc2bh1KXiYnYl7X1RhjJX+MOuksfA78tg/muNJuQld+CZr+Nhxogs9K0xSnzMXGfxqh5wJuSJVNMt1AHY85PSGtCTWvbLyvakikqaRVNm43meihF80PJndUwBff5gof0bGC7wxwyr2ZRN+KV1ELmldlo1KzmrmrkW13qaTAZDWBgxVrUbxxljNTrWvLUZNQQVr3MqZkEl5UPNirY5IkE/aDu6ZDpKNQgMA0jVeN14UBCLxvmyRsUHcjKY23IQDZoT/qlRSHNd8kINgCkfEkilRykqKB9JCBl2rg2ISNV8+ajHgQU6NNmnGoVJMlVnk99eWoqWRJSaZHJvCYUDvHLH/WjnDw1m39WZRTi++WKOzIZH/Kl+2RkMj6kCx7SVSA7oxrA9IsrK/pQJz3Pngutbl7NtMn4XBcxGRmeS12k/KU2RbqUZYCMzcQrAcfqdS2sasvglwlwCrJV8gDvs7GaeVXTarZlUu4FRA4HQ4zCueVTk5GmBUR0E5IBYpisgkHAMablUdiSKivgddhQASxoSmMULgEgM1G3tRWM5qNPHOqXd9koPzd/DVg7bCkhpVWikMgF6ZSRSkVeK+q1opyVqvG2qjrxHG3MaiAeevfMRBrTcwMOHABZQ8gYsIWOe621fSQwPloxG0WtSKHWmnFBV6gGU1O253oSX4ohu5STgYz9saOQaT9tLXlQsrVa1YogA+BUDQjVDLBARabj5PbYb0dTaqVB0vDMVK0CEmG0885fg1rHAEjgcDDjqLKpA45gAyD9CytyeyPaKVyl9i9oszLn1g1sYj7WKELJXa+UP5DS2mHLuZmP19LMx6UinV0U0vtpif961yv2z865BUHuSc2aql1F3TRk59QAW7xiU94aPFTYbLSQJataNZOJmETBGLJLPU0he42SacjWYn0875fVqpXsBjXTZuMeZO7UHX8fzZuPbmORybg9n4wvlrjLIMMg013ZXmtGtukJbOxLcUMz9cJPXuESdafiT71GjzDXhlZzJoVrdNYrehBmXZEWgu1UyIyE9BThXYhCautUBUJOueAuN7Ox+WNXPKTn3m6GFQ+p/XnIjvhlBaRiSBIl5D+GqqnWIvMMlYeMfbI9yBisS1nED9uCTJuLq4NsLbFf5iFjNatAqGZTddtJ+30dMZ8fVE2X4Sw/n/tNM8AGZ0ZmBVutBsK2c7VTVMlPHH088rRh9YxgA1DROgiD3zNjEzInCnhU+i00FAHXSe2kFDq+bozVkpCuKwVYclNLVrZra8xuEUjYEL++TioI0gArJqT/kC/kk5FfBqtkZ3p4LCaw0Xay1jbMW0GLOK4UhNAmI5uFDNUMMu2Tacg0XDzto4sMWRRd1IGPWyArA2TJQmZMyImabQGnlrEVcpKLVm05s6o2H/W827AxGf26umgAG5uGolxiKvK0LSfmnAKMHkMtwIBK9zrtmT93mxTIAClVsbBVQD/nK9DMyKXniQlZ035HZe4fua5AzeKn8V/KuW372iKPea3IVx2BrNZcaRUgH603VN8vCrL0bCFLBXep4JyAO1KxBSmorE1rZdi6yfiM7ntdCC6GTOc/KwXToBlFI9A8WNpsZKg46siqVhWAlcEDZL6ZkDgAGQxkrGbt0jFYTs34xnB5UcQR2HvDmjemLi61RskiH4H0sGmF8rCJeQgVIFFmkjUhoW62qg7S5SF1h5LyW9BBVZDrlsjU5LE+qHuUDD+wB9u6dhMyZYo0ujPve/eLul3JX0vA2iDDsiBfC+q1mY95BfJajZ/GJ7IHQtqYIHd5xV2+4p4ji0rNzqngIa24d5Bl5ZsVdxexmmmT8VLzLmQRcJe64FJOtI1Fgh7XoiOQL/PHtE/GkPnoYiWVG83FNl1KGiCrcn/R9a/q/uNpnQLodFJj79dxZYymYNi21q//TbDJMjrwdtOjQ8hPGn0g2mzUyzgvAe2b0c03g8BEd2ep0juEh9JuZlgmX7APP2Bg44bmNejDSG1yKJna9WyEskci+2s2DbLS2tNybqp2WoFLRjqTGbkm9Z4a7IVUXa9OuVAApCna+/yED/mJYLs2v4wgOxNgobmISupVjcl4IRCePVxYJPDhIYv8MW8uMkAzFSsBcF7FIlORISsKwAiyUlKoZIPJGKnUDDhTpi87+fzNVzLoAg+q5qcnsGlYUoUeP5PK8IF1xTJ+mX5qOHVrYCWa5j6R7YAqv8VcnLolZ0qm1Nalb5lhpYVrQiKZ1ccrp0Sq1cb9NqapPr8OOH3cKWfgcm2qdinIVzIftbQY0EjRUm1KtlzxPj/jvQB2wYf0jPu04iFVPEwg84l9s7UClx3IRjU7OaC0osUqNvPFjkYVt1TMQ1aKhw2HINtVs+FCY7gB4mAISBy8Wsn0y2DTyysgkcYBQD4oFdoXdfMKRyolGy7oO2awCjo4XC4l1ErvgbG61dobmUtTjFqgfhOpZUK6jqetn1t673hdm7nI/R3VazWibikBV/LVlgZbPS+kaEvz1zgoUtnkpdGIc8F5WXG3rKaR+kN+IrNxxUMqOAMGsiw96gtVq2JFxYUgu2xA9ljPU1Px4kDTSnYtmUBbDrWNaeB0l6zIF+s+WQzY6I+9EjIPnNy7zo9W6VUDqA5mpZ/egy1xBRVERZXjQUo9iAIU74NfK1Gv1RTOr6E52Z1LAnVtJ7iNu9h2NFU32jW4+1ZRfp+cnRb4QCHfz71mU8EHrfzFy9LMyMsJ+dqULa15YjqC1KxB1tSsKdqH9IwPAhrwkDLOKQtgOq2o3WTECNljPeEZi1Gzx3qeqhi3jfmI4tFgxxZgW2aiV7FS8gAY8ErIXpGODQmOWNV616VZGQhschc6sAYIsy83mpNGFkufr5XG2igKuJRInWufJ5+Rla6q11XAL5fynRepW0Yz9a7Uu2Pl80CN0Nd+WtqFbG9Wt3a/it5li76VkhLSNaEuC9JpQbpckS4LwcYRSPXETEDKXdHeLRe8X57FN3ufn3BPwY9zSgKZ7vVRUBpg5I891yqQPdaFQFu6gmHBY7nbVTE2E33I/rcC7EUqxvfpHmQbaraX5l2w6N7W1uioYBRkQAAY14WA8erGwcHYdIzytoHjlz1FyTiPADPfI5PBSxVwxQKX1v4GdB9IJ7Wgx5XUjXrh17TSxy4IGqB9YSYliS4CzVys+qrU1j2rXhuZKVF72rIgPZ2Q7ov4aWm1FzSnivPS2s/eLRe8z8/4evmMD+kZD2nFh1zwkBIe0mIg48SQXVDxXCueKvBcMy7IBFpXLm8uPpbzTYC9RSTxTQEDz/O9o0y+WyDTyOwon+uCRb6XvhfQfbV+x6hlRJCHUKLsUm5cdgg4KIjUCWh5/W3qREG+qrZnFI2eGrWCYIL6PhltgwMmeQc4MkWRmwK2Xvjcd5Ggo3fOWhWKusC1NXDX0t6hwwoZfPV6bVHHZUE6n5CfTxQYydJ43X3M1lD9QEGQr5ZHfMhP+Do/4kO6tuBHyjgTaEDzyVjNGLJHUjJWMTYVH8vZqFiDrcH1VM5TwLSJqAG7pcH51iCHNQtjwOTeU4DxOkbF0O+xXcjkXnXgBTBuf1pX52m4qpunQhIgYZXhYqmDFAIX+Wq1FzyicmIqqr8GFUOYuppJPpuRrYe8GTGYB8uJgOO8a2ndvOg3XUsL7a/0CgwPXZCoj3viC75KR2MADbjrVcrUZUF6PiE9n5Cfzy0CyfWh87IsVczGr5YnfJM/4+v8iPfpivcJuE8ZD+lk/DKG7FILHmvBBcBjTQayx3ruSlbO5JPdHQLMRxGPmodvpV6QZdhUMC6ngTAqxjeoNw8DyMy8S1qw5gOoqpW1IoHdBAdbWxSYkgwRr1v7BkXVeAUNkTlAuBNwTOWkrGr4Tvy96NL8nDadzNvMYmIq4OQFTRrjI3NfyFIJRmqwps7BldvG1vZbcwKuqcN0vSLV1CCrBbVk4HptpuPzBTidkJ7OyE/XpmzXqnzB5p/dL1d8OD3h29MnfL18xjfpiUzGDhn1dWkqhoLHuuJSKx4r8FgznupiAGMz8bGcB8AeFWgcpo/MQ69eR3ty3AoXgEG9wGWh5/me0eA4wPT9xutG0OkbHk7NPHwqBeH92jeq5KdCmZBqe8aHo/UbKMmajyrqoX02Bquvr0B+a+hUc4IOLrTpEboGGKQbVFqTjFbV+ipSNynq6Z9yQjq1DsLQ3apyFoWrFPiAnI61QcawXa7tRC+ZzMc7LE8F+bJ0Py0By1Lw/vSMb06P+G75hO/yJ3ydL3ifEu4DyB7rlZSs+WOPdcFjXfCx3hFU9OcA03A9UURRq5dWsWvJf3Zw8TINkDER9b3Fefr+0uVc2RSt78tTOnG+b6g2eYEpqPfrN2uAS21jooAeMFY5qDzZhoXOHFR1yxR0tHtwFFLgYpgqWtBEwcyN3W06hs6OVgWjcnmlt6RLbb3wr0W6VSFfGzjXBemyNNOQAh+4XIDrtcN2pYhkzkinE9LnOyxPd1guJ4k+IgHnZcX70wXfnj7hu+UjvstP+DonvE9n3Kf2/NSQPRFkH0tTsY9KwT6WewHsqZzxWE9GxSL14t8ILhmq4IUNywAMXDzN+ZHf1ZfRbeLg0uv2Ffm+CfLUetGy5Nfx0y4vfh+NCDEmZAQbg6JWD/bRTEoCThTNAQbebZSnNj5TOw2YB0/gDcDjIIpebzQlyYfj98NUZ18e46OuaO+RXWt71eXaBkzNlxVglbtce3ernIFL7mbC2iGr1wvwnFBPJ6THJ+THeyxPZ+Rrlifg3WnFN+dHfL98xF/mj/g2r3ifTgIZAFzqiqd6xWMt+FSBj/WEx7rgU7nHx3ongH0q93isZ6NgrF7P5TSF66qBUgGNSLWG11Sg4YmjhW0ZtlVLrr+HZaJcrsxmPnw+32MRrHZdL1zHxt73ebxDXuCUSsNk87VcjZWaQlZdnoJe1ncHzeuZCCTvQ/KTBSwAL1FPkz4qVe3qp6DLK0F3pnD8teXVEw1TcCmtx8flRO1kV6SF1G1ZgOfnVr/rBagV9XJF/fwZOJ2QPz1g+fyAfKH6ZOD9+YLvzx/xV6ef8f3yiK/zgvt0xpIy1lrwVK/4VC/4RCr2qZ7wS3kQwD5pyMoZTxT8eConA9fTeupwkW8WqZZu54p6zWvFsiC5KCHdF4cUS663B+8gWNGyIb9nhYD57U3S/H005atVB45uZ5PVfD0j6KhSN4PnD2p2oB4+dGi8eSr5apvis1W0HirK1OzvhKn2t9rNyqI+UpFWIF8TCg/1faX2sGtBJvMxPZ2Qzi2yiNOp+XM5NyW7XIGyojwD+dMn5F/vcfr0DsvTmfzEgg/nZ/z1+Wf8zeknfJ+B9+kO57SQil3wqa74pVT8Us74ud43yMo9flnf4VO5x6dyR6DdCVxP66l1uSono1rXkg1YWrG8KbjSsluhkkttlkHW8/fJAFV4P9wA1qTcEOyY7Utt06sZMBtubgAhDfGRoY5qXSmjFY0rxdupwbo0oXetT4gBY+fXVN88lfq8MTPVvA6smDwTNOE858fxH5mUeW3TLWrIHYaX1hhNIfz0dG7QnU6oS0ZNTyjPAMqK+vSE+ukTll8+4Pz5oXXJWir+8v4j/nD+E/5mecLX+V4g+1Sf8UtZ8VNZ8GO5x4/lPX5Z3+Hn8g6/rg/4VO7wab3Dp3IncDXQmloxZCsDphTLq9UMqlf5VeY6HlSqaFmwnSFFZXEArtm+4SBT08e++BkBp1XKJQODB4+WRfCZXfkNBWoFdeFScPINULwNlVddeW2CWpNS/+qgiSqjvgYDAS7198no3bJ8TUjXpbWNPRfkC4Xwn85I93dI93fA+RH506cG2fWK8utHLD+9w/mXr5CvJyynFf/zw4/4u/N/x/f5hPt0xlO94JfyjB8K8MP6Dn8sH/Dj+gE/ru/x0/U9fl2bin1ez/i8nvFcTnheFwHrUhZRKw2V7qg7f2ly3jgs1yGCaQaSvi5HYfLr+zRbBxtg7c27/UVKxmn7NRkNg9tS9ZRF62podEU1WJFpvHFwpu1N0RdCw6W8pOttVAW3u7jG94MHzk4LYApAPUYjClpkkl/mXIF8zQTcCctTwfK0Ij/eI396QP71HvXXjyi/fkR9fkb50484//Adlqd7PDxc8K8f/hF/e7rgXXqHX8sjfihX/NN6j3+6fot/uX6DH9YP+On6Hj9fH/Dxeo/P6xmPK/lf64LnsuCytmEDGKhSXB/DA6+VyHlTCvZiE89dwxdBFM3DwTQpc2Q7cfer/W2NA6gGpl0YTgy2XjmyGKxnzFK9TlRJraZqHZ8tdQny7LOh9qJTc4HzOpSmfKCOBjq1ncGfq1Aqx6YlmZQrGmyXBcvlhOXxjOXxoflkv3zA8tOvKH/6EeXzI07/9Eecf/0GH95/xr97+G/4Nj/gT+Uz/v56xn+9/AH/cPkL/PPlG/xw+YCfLw/4dD3j0/Wu+V4rNTKvGYVUq5QsMOmXIEtNDhL0cPlbBB708igdgQABPLN1X5Q/r9+Wcs22NzUdo/3MYAkLuR1O6711wt1mt45vtjAEGcGzQ0uc297M7h7hS3MQnfrZrl6kdNfaVO4ZOD2dcXp8wPnnr3D3w7c4/fMPKD/9jPf/suLffPfP+F+Wgv98ueA/Pf4t/u/Hf4X/5/E7/PHpAz5e7vDpcsbzlRSLwVqTQFT5BVkFz24XpOHYD/g9wfxsTI2bQTi6XModv88OpxvK3vQ+2sG6tnSwrP/iynTfN+z6yIq72ztwsONFCZ4GGlifF4KYejBlzc0ne7zH+ddv8f5fVpRzwsfrPf79P/6v+C8//jV++PQOj49nrNcFdU2oa+4vv8q2Y2D0TT8cy0FVGcvccpP0dNMN/pL0pbe/k05HgfhSqSYchvJV+7h9rf2rP9tuiqcrby9F5Wp7m5x+01KQlorltOL+/opv3n/Gv/7u/8XH6x3+/j/+G+RLxae/WpC/Sri/B8oJqAv90XbaL+973K85ukmdddo9jy+l5c/y+r9tuu0N6xsqfPjgjl6c3Yt8W36N9nvgZjP19cCkavMSvVJD+Zl+U26hpJQLlqV1EF4WGpbgtOLhdMXXd0/4y/uP+Ff3P+HfvvsH/LuH/4Y/LCv+wz/8b8jPFe//j/8TX337Dda/+Utcvn/A5esFl3cZ631COTfwyikZ+Bg8hk7gc9Pt/PRjrf444crpzJ1zOL3aN14/2d6B+ywBb3ef3bhvTvvDzd26g9kB3XoijwISlTtav+im8KrD05SfdLkEM5IWQ9WAqv1LL5n/CpbEb0bTEN7L2gbWOT3j/enSulWdP+Kvzz/jD+c/4e/O/x1/e7rg2/yA/3wB/suP/xM+/9WCr779Btd//hfkn3/Bw198h/tvv8L69T2u789Y32Ws9xnrmaFLKItWvNTBo18DHc8rcEIQYfNsvoPUbm64Rr7ckHz5WdHp/RQvGO5lG0WbbGteZMbGdHCe3ZX3FGGyrXj7O/C8BhxdZmayoUOilyelULw8SX4HSQPVx8InsOgjFEtq74/xQKd3+YqHpb0d/eH0hG9Oj/j29AnfL61b1d+cfsLfLE/4Pp/wLr3Dn8pn/KfHv8WfPr3D8lVC+evvkX/+BeXTJ9TrFfnzZ5x+fo/lq3co7+9QHs5Y7xes9xnlLjXYSOHKqcFUFnTQcgdQFE4BGKmfh6MySArSQ2qYemPRFLite0JP17GsiR67dabRddVmbNcL/PBkF9PqJo2diu2+xp1Mym7Nb4L0Fupj8sb1vQq1PKdEtFwmJzAZsOhPfzqJITvRCML8rbK7fJXRqt4tFxl+4KvliXrgt174f5k/4vvlEd9n4Ot8j/t0xq/lEX9/PeP/+vwHPD2dcP8APH//Dg9/8R3q8wX16QllXZEen5Aen7C8f0B+uMfy7g7lbkG5P6HcZZRzbsCdCbgliVlZloSaa1e51OEblC4CzsOnwVPXRfuKMsqafNdgUt5dz2i7ftq0MkX3prp1TMDZQzNAG1E17j9VW4dj4f1DqqHXPVBep5m5Ntu3W5Z82RfAxPMRUInWYZBygoEqpz6QKX/V5S5f6Ze+7kIq9j4/00A6bfiBb/JnfL18xnf5E77LT/g2r/g6L9J38ale8EO54r9e/oB/fPoW63VBOQGXbxbcf/sV8sdPKL8U1OsVtVTkdW1vaz89Iz3dI93fId+fUO9OKHcL6jmjnBp0Td0S6pJQlvbmePfn2LysRt264qXjiqfmWewiEAb1o/I9P8Xl1bWXduDofuHlDgxTdqsZKTnF8o3OAZic7FAGujJ6A5NKh3DtgXUEqleok5Th8rxcra8h4vU9VDxuYlbqteQ2Rj+rVfuSS/+c7Ump11l9FPCeAGujCLfRqr5ePssYH9+kJ3ydL/Q+WetSxX0XfynP+Kf1Hv9w+Qv88elDC+EvwPUhY/36HqevPiA9P7c3takjcqoV6Xptf5cr0vMZ9a71p6z3C/J5QTll1FNTuHpS0BnYRrOyw1bH4Aqp3ww+DZl+84PLGaii+0CpoTVTIRuwYI5+on/jRJYrSPR299phB+D0dpSqTXuGbCsJl90BUW/nFrDewOTj9Y9C1b8HrZXLKhaD1T9juwpk98tVPmt7p4bnvk99mG49XPeH9CxjfHzIBe9Tf2lzSVk6CP9QgH+6fot/vnyDX57vUdcGxfU+4fr+jOWrd+2dtXXtHZGfSxvWrpT2BRwG7u6Mejmhnk9I5wUQZcuop9TMR4KuZvLpBuAgUBmFY/i86gUqlzwwDrZIDaf3mduWvW+SK9tA8KomJqIz98y2oKBTYBoTsSZ42DgdG9dxBthRuG4Bay8gQeVFqXhelffmX88fwVpy97MyLT8RaKdckNEh06ol34qW31XGv+cPAN7T0NwMGQP2Pj+1IeFoIJ2HlHGvXtps75Nd8EtZ8cP6rvVdvHzA4/XU3gzPQLkD1oeM8v4Oy/sH4PKMVGuDDGjvtQFAre1jHOuKtK7tfbhzg62eT1guGZUULi0J9UQm5ImGXGA1Y9NS1K0qhUsCmwaNwevLkkDmo5izfP1ANbC6IMagcOkF4EXQaYWaqJwWtVkaOhVLBXgLt0C2BVKQF/lWr/WrWt62YvHHIbJaPlOtjLoJ15lUjb+oeU8fltCftX1IfZjuD+mCezXuYjRaVXtps73q8sfyAT+sre/i83WRu6ycCLSHM/LDPdLTQ/sAR6kCWftMVOkf3FgLcFeQSvvDugLnE3AtWMiUbIqWUdeEnEnllmZSItc5dEbdutqxWvFDlGFMaQM8r2wOJFFALqNuIa+UPs/CxKMIkIkJm0SoeIZh5DwFpcA2UbWT2WK0F1PRAECoo9QHFsIaK9cWXF61QpU6ANZMtVipZNrBxdNnUrP+u4p69U/YrgNg/AklHtiUP5/E4y760aqayXjBL6Xix3KPP16/wk/X9/h0PeOyLvzlX5RTwnpOWO8XLA/nFvi4XuUzUQwZj66VANRSkGrp6nY+N/hOC7AuwHVBYtjWNnJXWrKAVtmUpNHOh4Zw8eOqMR99k0GHq3aI9sBzcHkoBUh9q00AMwpGBUQlUw2Bqy5jgI32OZielBePgqX3oCGbqdgBwKb+1u8E10y5tIm40LRXrwiu9jnbBhh/zlZ/CPCePjjxkNow3Q9pkcFN9WhVTc3am9E/lvf4pbzDz9cHfLreYV1ZDtpNXs5o7WT3p/Yu2+XawNGQ6aHsyOZpY1vWZlaWE6lbAU6lNa5dcwcuF/pNqCV3mJaEumqV62ZjAyuALqc2GrqCTkOUlKkJ8u+0/zb8oW+LAd2CjgETH7EGECKFwBl147ykYDOFeIM9zYcEVzDNw/V1VCwH3ZGeFFJcmYWhGfgCuLRJqOFioDJFDXn+nNdAxehPTzvA7vSH2d2XNh/o00ln2A9O9BGE+2hVj7XgY8lt+IH1HX66vsfH6z2e1hNKyXLuaqYeH3cJ5f6EfH9Cej439eKv1/DoWgAqfz+AgEtAMzNLbaAtzZyspbQxTEpu33vLGZUGjeVfEGQNsEjl2o02+nBV5lNCh058uldApxQv+WVQ5qUHDGpe3coVaTQpiZ+qChq10yakS2YogyElNz2DzKuYNxEngAmDDrC38rl0QEOmU91Vrw7aNmB3BFVTt2ec0WBrH2bvkJ0T5Ptk/oMTAMyQcJ8qZCCdNvxAe2mzvfKS5Fq1BmeC7ZxR704thH+5ktlIioWVhh4HZKx//g4wAVdrQeLy5MvV04JUF/rAYgGWpSnhKbfXbHJqwZPigOMPh4jK9cAJjwxd6Qs/EiApECgHc5E7WidrWmq4urXjfDo9LYqlbm0HnDYF23xbUeDi+9fNQ61nksobxt73hasGypebQBb6YAcU7K3VS0cMG1TrYCp68zCnOgWs/V3FZDynq5iJZw1dWnFG+2Y0f86Wv0+mIdNj4fPgph95tKpyL2N8PK5tuIFmCqqbjEG7yyh3bbz+dHduiraW/hnfVCFfsCHYoD+sWDPdZKRup1OLYNbaxpesC30MMbUymfy2KXCpfYGHAVpAyzkvKTOuD0WoAycSNKnHVc40HUTAOS74PhxMTLMs0XSN4aKqGJOydkg5bZqOcQ/3g5ApwLgyxgd7I8AWN3/EPMyp4ExlbgFMw6VVrMO2dhVD3fycLdDHwn+sqwxuyqMHt9Gq7mR8j8ua7XuXfANzQ/M5o94vqJcT0uXUoouVQ/1X+bCGrM9QgW/AZlLWTLWsS1O3ZWllM++wksqlfeCqA467dNUqpqOYkbUqyJL4Ujp6aU3FAyo3A44Vi2HXPhwcfFIuGdgkX897X02lG9vRbodsCzAAA2SZel/8FoB5E9HCdjWg3SnQHtKFYGt52lQ8p2Igy8Dwpc2Vrggr2YWG6X7iwU1p3MVPawON/TN+M5pvippbr/xyTiinjHxeqDG6BTjqutKoyxX9wxqUCptz7fNT5ml/BZmSC132irpw8KQ1aKfazMBUG2RYSG0zgAVdrRi4OgKnARNFy+ggkm+XlIkH5c9tAVe7O6uj8AKwh1D8K9j1ZHoGm+ZkI73qi5+vgeyIii25DoAlzKOHGqiZiciwnfKKBcVEEZdUdlXMm4sNtDJARh3jsWBUMv0RwMda6IMTbZjuj/VOxl3kIeF4ZCofBjOqRn0YE8NWSmuo5sAHAKTSzMFSTX1QyQ9LCfKFG6h7J5PvlmvPrxlYKv3SCNALPwFI3dimyrV9daeR1ZaX2jiuqYX8a7VKFgDHd/ZM4WpOcltCRTcHsNTtKxAehe2FKX5NJgW+mVezN4BMv1YyU7GthuWZD9aB88rFoLUw/YJizMTsQLsbQLuKqbgH2ZlVzAU9APsRwPbppEwfnVDj4Jc+JNxlXehTsakpCbpJVXQv/FMGThn1fGqfjjqdCKIqdo18eZSSmJA5NwXEghA2vg2uIN+tNt8ub6tb8/VoJC1SOnN3LxRs4M8oU9OAqGMC5Sd3PzqIMtpxBuomZZWL+2LYMFc1fo7sm45HiH0FZAasQMV8J96ZmThrYPaqNvPDjIk4KFmsYksqu5AtBJn/uqZOGrLHWvFYE310wo6F/6m00auey4lGrBoVDfxKCwdFKAK5XHL7uMaZghql2huikLIFqZKJ11yDNYYN9uZjYCJ1qzXJV3k6fMpXM5DRupnuo9obu4UACTH2v8qxHScENScLEou2Wk8fzy2w+XYyexJHBVS99zdW9OoWLNuCLOe5qbgcULGXRhI7bLGKZVTjiy0oIWQaLi6jIVsIsowGGZuMnFa6TKX2D7PzN6Mf+ftk9OkkGQu/tBGEZbTgkgbvWzcQV+kQ3BqacT61D9XTXwvhU0AlpWYKlh4caTdIy6s5t0AKRSfrGsCm/DYsGQkZFcX8olQa6lytQ+rWlqWmEBNzUqIUSsVMnronvbpVoG0vdd9veECodrw92PwJSPWAWakarreHMhjP7qhmqvwtkOm2LoZM95pP2O8mdUuwg1XM+2HaXLxzMO1BllGxoLKwYAlOY1HKoSHjb5S1L23qb5O1D0480zDdbQThPpAp32cassLvky1ovfDPC5Zrad2qVmqMruxf0Te1yVycplLbhxVrAlCaMnFDONDgWtUng4EOGZuSC62LLJDJLZPUbZzUnY3UfDoBTOXLPdnVTauZKJQBiD4XzYqXA7OxzGHjCg9geVUzBI9Jvo+mU/hGtCfam4xUG28uHoHM96DXpuKRBmcP1qKULoooatgYNO2PLaibkImypkoqFp9cTqxol9qaii+VPsxe7eds5ftkpUUau5rlPu6iuya9J32iKCQFIk4ZuC7AiToQU4O09ApJqTVsA+K/halU8X8kSslpBlsCEgPWNtJ8LPQbuz2VEiljm5YOvlpSDHCkdAJNbW17BJBXKF1O2sPoazyDWVjtPMO2pVyyzF2W6GzujxmioVNqxvPGZISHbPTJXgLZlqm4FfAQuGh55I/lVDchW1AFsoX2txBkxmSE9c1WdboLWkifIbsg4QIHWenfJ2vfJssu4phGH01g635aPuX2qsup9VdEWagzcaVAyCI1TFgoCulMSChfLasG7kIOFkco19JgK5W0mqqWM5mbCjb98M9oXy8F+VFrv58qEj24W4AnFQqEiN+YOkyqF4oGaFCogl3YMANKm5BahF0Zw42ep+nj4X0FnOn5oeYTlRtD+B26GWQM2JGo4hF/LILsnBmkfcgyiswvZCLynzYZo+RvWw8Zf9b2GUv/ZnS9w2PtH//TkPFHJuTC8TXkDry5wyajXLGvds2t7+JKPT4A1KvUjG7KDRNSdlYhJqTMQ/y6pmS17QcjbFg6XK1AML0kUs7mr3k1a3B18LpyKdgUhCbS6GAbfLDZvAPIAtbNx1QR+2mU5lHHpH7N9Khmsoh3OoEsAQo4GCXbguxo21gU9DgC2aKhSgUZpcFGgY7+203GKK21iqpxo/QKVjRSMjIZ+8fXT6JmT6xm9AmltWb5aotRNJ7Vf/r9sFNCvTRTsqlapr6LFdzjozv5lQIfLYejkWkWOdUmZM7dtKy1mZEL5aE02Gor62ETRUIL5KTS76u2nIIjuQ2XjqWZibuwASa/aoAqus9WlYkI2HltMior1igYM1ARK5tTuXkXrK28mbqlHiBhoGQaGiyrcEMvD6dkt0DWTLs5ZLytu3Ql1SpiUnIIf6HtLSgGsiW0vlta0cxHDRiwAVk944LFfJydP2nbPv63mIjj6KPRlZSeFkrVGLY101giGWl1sIHvF+oxkkmJtBznjUe0buQWs07lUxw/raCeJO3zw1jaSUkgNa6gMqkDVGGU7UWwMTh6ucDUAzMhTFsgcXmoZRuAcdo2HRVAkmV8sb7fTTXDCJkP4fvAx1uZi0sqBjJWMKNapGLN5yrilzFYHjA/T7cVVpe3VvpVkLFf1pTsDs8EGDdSX+sin7PV3yebMd7VrEoEMi+VgiLtfbKUc3u5k/ouyrUE32j8NmkV4HohZ1ZWiWTQfDPrzLtupHBiXpYEq3Du3swdtgZeHczIw7BVMg+dkvFhim+mBVT5Zxq4mapZ+FTBw6YjEHck5pR07WI1s/0YR7/MBETgzEeM0UXdfibqx+YcqZ2GrJt3RQIfWSlUU7CrrNt8rQ4bAOTUfzVUW2bj6JeNkD0j4xkL+WRnUrYWabzQ96H1B9n1h//axdHXCd2sF/OR/6hTL7et0UA9qVIHYe4YTKvXlY4gw/aHnCU2H/mpW+lgFwaOfsmsbI3mySlcotdlksCZmsXZAyQaNgNQu9Mr7TtRvjYPBUbK8yAJkCrPwLVnHgZgcTktipzC4ebs2v7XwQYLFv/qBnzO034Z0LtU6UikButoCN/4eCFglcxAXt4Vi8vP1IzrqecpXtemA+4YsLUmFALtGVnMw4uDTf/pb0brD7DXOl4g9s/aE0v5aUsP9/MflvaqS+txT7CpS8s97ZvcbD1sTf8teVdN5uFUjczKBLVZho6AFJ9prUjUg6Si1SeRKVkLkHIFaLi9Dgya11WShPi5/azDGIOUQA3a2gSkEyLQOFWLfg2I+lSp/B3T0f4as5G3RL9+mVczNhkBTNXMqldxEJVA1RRAUICpAMaitsUmo/heymT0asbJm4lrTaJqY1CcykwhO4nJeKknPNeTCelf60KKtvSvbrKiqb9BzTJUUKQBh1xRT6ndmKcWgm/vk6lXXfSlXtcGR+EGqY3kfTc2H/U8q5rMo+2fOih36Bq7LWjRhzoQUKj/YgI12JNaAT6s38obBTMwYgRJ50WmoVItA17we7PpyBWZpgl0RsUCNQNUp2HEJqMPfmjolgG4YiDjsgBEmbzJyGoGdIAWBZZVsTJAxh2MgAaTXofnGbAVDRINGYfyvYrJnzIbV/rrEcfokYnBbBTwSN3KkpFX6tmec+vESx95T1e3uVKAVLu6AZB32JyvNkQltfkIUjVuyafuVt38qwq6bkIyEYkVzamWnAMSXqQalMNoHrrlWqVSDVTN/TKAh9IEuAPvozn1iooo6Lwv5s3KvPeL7fzFg+hMRoYQ6BDw8sEHQ/+dAcfJmotJ6sLqxWkG2XPt5uIzBT/YN2v+mfXN2i8opjC/ylrdrI9WZRwPkK+WKtrNt7C5WMd7orT3AXsP/6VD55UsagLQ6sayxcESjlByFBI939zwbCZGJiQ6HIPpJtuy0MwgivJlM0AH1x/mAGPa5APYbEcLVgz8M1m0oWbaN3sLNQOABUV+BTDlZ3k1AyC+WZu2MM7SSk9EBr7QkWVUAYzzGLCVYLvUBStyUzF007H/LT0IUikQUpbWfgaIb0Z82Mcqi5yoWrvYtksW1GhVLTiC0l61Qc39/TLqGCwXkF+dIVD0azWDkuUcA6eTNiVVhHJL1bhrlQ98gAF7K1WrbR8S7o9UDUFepFxReT5N22eIkr6+gX/ml81+X6JmUZTRqxnQwYnUrG17VCytYjo1YLKYgwAMQECDq6B1peL8CLKLgSw2F42i1aZog+k4SbKYzUatbPIttNRUjczHSkMQtJ71rcc/Es1z6Dj36ZQzUkodMl2mX3x6Z2wbOhOEcT5ckl+/HE3VKi2rtIym9Tpw2xiXH8s3z9/5LW/LbaTtvo4GsHHag6SnOyyz/L7ulpqZdQI1M/kDbFa99LJbEpuNpSZkMhc5cdeoDhuD183GtWYxHZ+dmrVIY+vFz2bjyqF9sOmIGLbUfw1gCaJoyNWM61GXrmg18w1LPhv1XZTQvFEfd96yUsAjify0No3eFCemZFcYsd/gzEPAqlq6QdUCU3PXpERQVp/+oNwsHRszJJrmLAeSLubhsuZkjxwCx3yzaLnAJRDycgubn857kTVKDJnAVe0y/cuQXepJfp+rNxlHNWOT8VqWDpkP67snp76obELKrx4bX3XNSgo4KOBkOwBFJ7lNDR22ZenQAeOTd6sXieyg9vWiaYYx8ufU8n7z3+CrDWXg4HJBEQRlzbH0vAGyoPyLxwwx/CX726a3zcatZSNcviF5AtuG3zVraJ6llaILORUTYfRwATAqpmHrkM0jjWwysilaKLjSAiEqtB+l1P86ZG5+QQuKGMhaYKQFSioSNGz00ia//MbRRMAqHM+3E2/njybfLIDxhp/DhA4K9svxy6WHgiIYy5i8F6TToRX1TZri/MiM3DMbbZ6H6HVmo9/P0VSoO8GCIrD1gyy2HLSqNciea2ut05CFJiOrGTVMX0uWv1KTeQetDvLlZgW2dteY6KM2KUnVUGFNSIZLttk6CEuSHh+wTWxaxZz/ViOF2wLRKBxuNh9lPJIQMnXa9sxHs/8gb2sacxPy+MfiDWwjYDpFN/hgTqrH9FuZjTotO6Zh0S8vqenmiznYODm42nRXsbXmEDIL2MmqmfrTJuPQI0QrW2o3Wk3okbJEh+HUTYIiRasarcQmJBxs3Au/Vhmurp9YBZ0Hh4Mkfv6oaRlfqLcxH/kczuCCLWMOKzInJ2WjlOprTMcdNfMqpqcjZZMyB83GKO2F6vfSSu9uaNjMcldeRybXmnFBC82zj9YCIoHpSGrGPUfYdFxVY3UFpv6ZSVyEALNq1j8w0X23RAPlKBOShx9IaB2Q28EBMmJWssDNlIny64HoY7h6VYcamJWm3AHz0aQDZqKsD0yVaTNtgHes9z7PHjDFjGW5AdSWOXkk3Vq+dZ2aLCM5yCgjbLPtKcAKuqLpQEiHa4St1IRLWVCqbqBOHMkW/6zfeJEpxncIhj+Jc6Qk8IF7a1RYExIUgQQNxJM5EkK+Wq0WuEmq3lfzCjfU/8Y7+UYfKfLTqt9nYF7eOt22kwZedHrVAKpRyL9Nz83JUMUO+mdRmreFZWSnQevkXXfeRnGwzdJKAGrACqgjsILsuZ4kzF9qW15qkpA+t5ux2RhGHHU7WnQaVJH2Rxc8MB9bf+E2VICU43Hyl4Q27ICCTYIhtQOnTccoRZExVrhEg6pmhJDNFCQERFZqx7nnp4XrRKp10Be7Nd0W3sftD6EQOsyh20p7ftdLkvXVAGnD36haQffVNGS6kfp5I9rIasa98wtGv0zfy2HkMQU3iVOzmsh8JAAjVasA9QqhrlcMW0UfeuBAP+NeBwfaUTPyDSKWm5vfAO9FZqKpy7hNn16kaNY81NPaHwvWe0EU8Ja0mtgZNSar4WkXrIOqLakIbEvSwY/YbBxMRlKx5q/FkDGEuoFav0V9Lb1HSDHAbYsHAAmIzEzH3pZWjaohU7cjiQU52EppClFo3EWtbj7Mr1OkZJRv1GxH3V7i492Sfks1Aw6C9tpjPrL6S321tWZkNepLqRlL8mELLptMexqH7zVsvdLjI1ybjDzPkPWw/olgadFIiTIKVIuo2ZXKCFxAe6Oad1jJsd963GrA0AFLHrwM+tILGiQLqSb10Ggvg9L+FoKtVgAFtajxGPXLnZG/Ngn5T02/2TGpdNO60Op1QPVuhciVP6qGJyn9imSV7MagxisjhUB7DuvBS6X9K8H4aQ0mfgEKvTGagx7GuYVdj7etQvysYu3VmA6ZDn60yGIzKdvYWomCH82EvNY+CI/3z2z7WXDgejGpWFJ+WjcZK30EkAfWAd38DS4e3FQ2S2N7aF+tMcfqlgTWtnNVucBxF1AiNVP1Rw6APNYbdzPdbBq+sZoBrwmGHABqC7qXNCbrAEdxUcSVenH4pM1HDnqs2qQEunqpKOMaXGHd1YrLrJW7XOUBMtsDpKvZhcL5DBtHHbkTsfbRDABq2twLynwU2DKaSUjPFgZM+kAKKG6gGt4Xw2Z8NepTSKBKp9+JahjAuNxe25tfZuY3lh1JW9C8EVDjdttDb38og6PL3yi1jrvHykZmY48o6shiV7GmcqXDBozAhfXqcLV9J+Wj9cji4JcRTNwLhM3Ka6G2M9OBuL9Rza/HmIbqKKX+y5D56e6z9fE52Cxl10sOXwk8Cno0j9WsVmqHU9DNkgZM/Y6+GrqaJfQ8lW4xH18V2NjcMEar5+C+Xvd9tDdI3B+Be8ZvlUFQrtCdkSd+mU49EEIZtdDLm9uRxtWYjhaw9mpMFsh6e9oyQNjKuMCHijiWCgFu6LEftqP13xlkBjCGqFJ7GC2TAAf7a7b1oympNx85EXRhigAD5gGQIAl8Ji84Bxv7r+o8/V7pdwNtCyxbhqc7TGwOWv9L+1qxqmWGiszIgkwDNZFJiWXofGzfntZBkBgy3cWKTcamaNkEP65q2dWYjMFdtXGaBCqd2DdLFVCmIyrk00WVe4coE1LfifbU0UA6QDMfSxpNRw+bqpRRIw3Zlpo5H46P1QZb1LI38OXePKlT+kVBKy7Kd3y9Hjm009Yva++CbauZDoyY8S+MQ6K3OdmOMh01YPodNIaMAx6mcVpFGvVQcr03yNhQvRfaHxKrGR+TMR2poTonVOrJLh8BRKIXKknlZNwPSO8S7sXP6jaYjlsKpSFQPtk0ADIc0w2q9lLV+sJq97ubjjpplVtn0/SIjszHfmdApk1kUZmMdti07Xqx6ciAtekOmfbJCpLqmU9+W1lc8COL2bg66ACIjwb2n0xAxFUuqW+A0T08/PKpUfngjh8cdVRKYQbWqTSP1J5PPBajqCHmpqNsMJlpORwNWaBmEYCyXOZn07y/7ar9Vuk3AY0vQ6WnYQvH9zeWjVmIPtKUn0ZgPjaVCoIgQAwbAKQ2HqP0NPGj8VIq6gaPAJPfCWTX0gMgHbYsoxBbZWP/TAVCZidS+2J6+QQ2OfTa1ax/M1oanWBNxwZbogF+JGhCJmMHDv3G3/HVNGBtfgeypH8xmo03qJoHbxPEt4JTbec4aEPEJQWP19eYi121rG9mo5AasK3gyeCv8TRggAP6IKi6i5cOgOh3z/w0q5mGTAc6OADSOw53NWOgxvYzqmZNsDbSJE1MRjYXQwD152xLL4OEYci4VNEGN6XwSCXzTz6WIR+oSOaWGKoeAUbrzfwynbjM4Mb69rjZ/l+StgC+YfsdtFe0I3BHVZ30EBGzdZBqABhPWz+tOQj2OsxUrQU60gZgY7sZYBumOY1tZ13F+NUWhqy3pS1qMNQGF0cafVeraSO1uWM2zqNSNZ5mYDRYBjYKjIj5yB8FBPtdDTyGsCIh0Ttt3CQgwFXImI07VQ0Bk0NVkO2qGWCW67w+nYb83SaCL2hmvqnpGAHngYqijbPw/Up3ju490qFjwHAMNmAArMC+ke2Tf4taAwagqxnB1X/7cN6rgYsCKbrbFZmNvf0MkECIPk3RHRzdZGmcNuDxR9pZHTKZjvTLAROzT6pLoqexAS4B0O+BzVIAQTff9iEzahYoS+ifuWlfl+iZFtb3NYnu5UOg+S5jpinKLWt5I3BANysj6Lyf1rpI9fWkC3mC8dVkeeSvAXZaDl6ZiHUZh/1WZ1lgEziTVbMAsjai1SK/0vtDAcYvd4qiqXO32/XKJ39jKTWDNh9JyYyq8aklsxDoX29hsyStpHS8Pn3SthJk3VeTg3D1szeIAQywgY8DSmbKeLNxqnB+3+NpnObPtokJpEE6Sekv0LNeq5n323RABICAx9OANxm9adrh8hFJgQ1A79wHuSorKV6vS5w0XDyvAWNTMYKM/TPp20gwajXb7dsoj9yNkxwpmZ7XJqP80vXO6OF6XT6PsLVoTRJ1QwKZiwmgiObuG9h+mVMxPT2oUuCb8XGOJmQyQG3C9VuoGl5gOu6NGDZEGAkyn++nvfnID9gtVRtMSMAqG2AUbYV6ybMumx2aNVx+fgsyhkuPo69VTSvYSsN++/fQTK1m5qO7EZPOFzVD98/YH6PTyApUnZoB9GklB1vKiRqu0Xw246NZ6KbJqE9XMD+vlWwwGXfUbGY2bob+XR2+BHT7oB0IksxMRZ9ik1ErGsGDWNXajTaHTVTRwJcNYLbjsH1De9VXDgFsDrA+3SG7cruZAotVbapmgPHPoKA7mvSN6Ps4ghTM5HPUUeWByy4BbJ1Dq26kbBo6Trqr1hCICACT4zgK2Zaa6e2Z5Sr/6HndSwfK3KRoGqhZ4CMpFevjYSrlUn4aUh9Qh+cjVbNw+fkNZQMMcMAIV6n6BZueNFxtvSzTGrJr5TelqX1M+WOtzUx9IpcA6h+Ax2A6hh+04JvaJ38TuVU0WF0poHwzOaFQJxcoDrZaWxs/KC6Zk4T1m0pa6Hod4sqZfH/jZ232HYNsqmYOsMiEnKtbVO94+kjaBu2A77anZpGf5s3HFv1zCkZp2lZWJ7ABQC1dNRP7Zb2drNRlY7v9DOoeIfyrVawPdtoh6/6Z6gGiVM0rmla2fs4A8dGOXNFEdru6SRKs+ajb1OZ/7bq006lgQ0LKVSluq6QGDgkdOiB+MADxTQ4MgMlyB9lsm4P6mWXq3G6p28ZDazftcHJDg7WCLgBQBn1xv0BXMY6yxYEPZUIEEUivasbUpHXaJ40nwAHQPUCiL3XqpOECvKJ1yBgsPS1+GUagWM2GL8XQbwU6ZC9JGhyaZ3WTm1CrGgdGOB/qVRqCrTmUTc+4euKQU6fkxHWXxusDddUmIm8TsLA4yEI1c8e/p3B++0PaWBaBeiTNQTvgmzFw+qXbKCDip0ulwAd1x8q1a9gAHh9QaEK6PKCrGzCYj1EbXpQ0XHreq5j0V3SQcT6bjL7LVam67Uz5Y17BWNl2kjET/fzkz7qjdELpfTRpqCbYEqq8k9bazxpVDJwZOmBJew93qWPfvQdOH0uy9fWQeTXT2/eQOrWz5YM6RL9baaPMMUUzatY2OOMw8tMy2RX+Rtcq5n01OBMyhA0uj8pxRJEVrqCbilF3K2B8o1rDBcAAxss5uqjB0qF8bzJWIFCz0T+LAiGpxlexJnUq6EaSG3/46+o1A1FOu3tJVD7oXpopKf6YQAYLnVTQH4g9jtmNbaKQ2eXPIEsjTLO8LXWbGhMRdAdV7bbwfkBXV7MxUBKZjzwNQFSN1zG3/hHYhjzYfPA20M1KKRUHQVpZH9JXiqZUTM97yPgdM206ajUb+zXa3zYzraIs1pAN19wrhIfKQ5hrbw3RsAF94B6yEQfg6DoIdFKHjTsxuGGHKKQ2FWHrPYPMqJk6P4OpGU1HihcdwuSwIkhrAk67JuIBuCKwtPlYUCX6qAMfgFU1bULKwWzCBrC6NXO0wgO3QgN+rO0MsHBxPRkwzve9PcyIVm6ZV6/IbJSaaR9tAp4BywOlp9UNZhqrnaqJT5boc7sJCrCqLHbasQbORx2F/umpdjd0GvIjFePjPgzZhpppiML2M6duU5XbWcbpsKLtjdzl/TTAqhhDFqmaYJTG8fN7f8UINrcFBZyOLGo1Mx+tmCQNl9QBGFRMq5Q2F9fSe4SspYf8jZrRORs6EkeBkIM3rMz3+95FHkeT0fSzTui9QThgwmF9+qY093GURmseHRgOuqhuO/XXflg7HaOKQY7JQRZsN4TQLw/qEZqIQToCGKcRNGOPjDsT1ar0ZORftYxvHD0dqRrfyLp7ljchMwVMPGwF5O9VHa63ZmNXue2QvmxTnbkts5HLNhPRvlHNkGnTkfO9mrXj7cDx8feTccOVVJ0NzaUJVM50wSrqJpZuog22BPT+kUX69nfzkB8MpGQaOgBbYx21emq3OFK4QXl4OoDMq5k5N+oYIzUL9nGruk2hpXQwGIL+eOQ4rn5qKhXz5mOkato30/lcycGE5Mp7ZdMHpYDzCuZVdC/NzEaZ1qbiBmRX9VWYWlMbHDUwI1G7woF/xfY+UGd3oySdH9yI0ouf27/0cyyCDSCFo4teLXCzRutJX4AhbTZgOxXr05HKjSbjYBy8Vt1mvztpI7zflWorWRWrYj4CNjgCdFUDgvY04DBsGqTeMM0V4u3HpuNW0l+P8WajBozL9sFQSb3g2s3MenC+WaBeGjBsTJvz0Vf3gEXmo4dvgJF+26luF7MFPtTuVBuaUTh+Du81WvtjUKfA50eA6elInUKTUR+nK2/27x9Mvl4Hj8UnC1oUGPEmIquZ9tkC85Gno14hrGrehDwMGzCom4AL9yKpMh05hcEYlTRc/BsBZnp4QKlaTeKXDSYjtJphBI7P5x5k/nxAmYoI8txN1wBJ1oTUbxjp4Ifyz7qPBgMc1G0S+Wj6mR3euBFwQdtWZCpCjmUbsk012wE+rKv8BhfIrfeiFz8HPw1Wxaqc7VjV2vdKjsGGyt+jbEkrWI8iWhx1e50GTy+PkvHRFGTttwPG+Roy7ZOtVSuXDYDwJ3Mjs5Hnb01Gzei8yaXxgCUFEi+jdZqKKdgqJIzfPDSlkA4402hNldmFK1o26WU/n+4HfxiyLTVz2/J1ecHlATADTdsJ6teqGPpFMirWzkCkaj3wfgNsbXOxutEy30ANONjU2dmDzsLW29NmgJl5p3LyGoz57hlGNWMFozwTaDiaEsB9HrWKCUTuRpIb0PQC6SCJMHH0UerY6BqAk/uk7eDWhmvAlfc3dgDA0A3rVshmajab3wIvKKPT7YrmVEybj5V8tLZMk4rBhOTEAB6BTaub9vG0yajbyiLfbCsgYny0ifnYlXmEbK0eOkxMRqtmXzx5VcNoQiaipwLtRQhRM//M5ZVG4NBvDWtCAiFYQx2h1lV54/yoYno6gizaX1Ten7O9uh5Nx99H0/6bmU6o3MiJEbBwDBF0VUtK7TxsEIhUInUDJgoHay7612DM+CPBGZuZj1uA6cCHQFcUVMBczeCVrasbT5vuVzMyNUjqBjL9wDkf4zT7YgYuUTP7x+1oGjiGTKqq7xGu4hFTchO4JPORisk6AWQzkzE6f15ZI6W19YoPRecPo2AlAme6pg568CNN5mFUreWrGk1MyE3Y0NRtrao7F4NECsfLInMxGggoShFgfFw+8ij5ByAbeut7X0yDtZUYPDA0ZCayVRGtr2FiU5/vMzVt+jA62HjX+vHJz1Id1m8vf7oVgJf5aVx3WLhMuQg2fcxbkHmoon3fApw7huhS3NypeBiopwJJ2wwYVc2f+Qi2Nm19NgCbwLXt9ToydEBX0pl/NjMhtXLpsjPAePkqwRAIVCYgUnwjtQuC0LQG6kVJ+2lVXTqtZJxP78oyeECHjWNM6vRaVVN5bTr1Oyyht6X5QzHm5Fj9qE3NbMdDxcv88gHEDciidfy+ZnkHmsCAW178dOYiaZft26hUbdPeDGADYAIkDFROpFiqWnr5NMLIiqau7LpxA3uw9G9V85IHq2IRZHEApF0pPl9Svequ4I3OW1M5tR7fRBoyp2rdbIQdzwgUZVSmo74NZGV9mVWdN9vSZpfA5UfqcQgwPS3lboAsAs7va6OOs7QddYymnXpBTHQyOb3icDGvcg42wEYjARsQ0cAJXPRrzMpqw/kzUzFK3mTUeRFgAG6GbFAwPof6ZtWn7whw6mbnG8J0wVLwabiskiGGTW+eL3218/rS7vlph9JEyaL5CDpjKnKZCVBRihRxqN8Mssk29xusg3wxF5WP5mvqVc23r7VKkS9mVIkBIsiqDYh4k1JDx8u1ch0ZNMg3GEdw8fweYBV9XreX8bxXM+uv2XPYpzcq71XMT3sF42VcNLnnKLefSd0AiTA6wNgEHSDTdcAx6yoy0cJlBwBr013F9DIP2VH4NpVuVl6l429Y8xn0O6r6yadUDTgMG4BQ3SLgtHrpEY25Wl7RbvF3jKK5PA9Ymz4GWfPPWl3EdHTmlgmO+EocSeYGZzkDzCVAv6GSWi8yYGxev8YClJrmFSaX9maXc2qSTVRtAIyXOVU6AlmkZlH9Wzl3gTaO8wXtaG2L5KEBMvUK2IBQ3QALnEAWQAdY8A4cez8clbbMR1YwnjbwqTyrZDCQsUBoNRuh06clUDsulsZrrW96wxvDxSrHRSXiuAObji7SfiKzUW/E3KB7D43oQkWqNoXNAiZl/PRLIDugensPk+3XZGQL1RzU0aRD/uOlC3amzcIIOEAilBo6wJqMR8zFqK6yrxC2Pj8DrC23kJXCMCmTkber1ayq31vrDgWTwFUBHZBguCKxm8AmhapWJwWcg2zTbLzh3pkpWpQ/BYzyDJB7EN2YpuAF2zoBsA4sMG9Lc2dyT9USZrD12rTmgrZM+lAGwPGyVcpDlA5wYf/grB3t72iBs3kRYJw/qlgalEzUS/4CNdP1f4npqE6xVzVdLoINqm466MEQR8A1yCx0wIbZGCnwJM2BSzbvAGCyPFC42XozNQvNxsnh8f62fTR3gJup4gbYeAde3doOGaoKEFzkgznogD7YTnJPC/9thM3Qvjs7GrbBfFR5VYFyC2S23UwrG+y0PzVR8s8up15yY8FBF8AGNW3NxpYxACfQJljIqoVE13/vfnLLZ+1qcxPSld0A6RBkR9NO+eMN1sPVbNOiaq7HiIaNt9FhC7Yj8MSER9ABXan45vUA3pKm5qNbPgPMLNuCjAHjjev5oVJ9MvkbNjiVNalyqdscGgSZ3INtUDEMwMmlVysPbWi33LD6+CbzA0xRnoeKy0xgCoHz5ZSa3Wp2qi5YCTM5nKbaaqJNSKQRtrZ5uqqiVqxMsiEYNSMTsZfBoHRAVyo5VqNq28cTmY9GSAJli4YdMCpGddiDTNRM79jlzYaYi5KxD5yKcV5oT8xg01DR+tLgXXvhWbuZgU9XcisFhzucAg+GXm9L5fYULljmIbs5qftvbEfTFTfLgkeouipbsLU1RnVru+wwebg8dADMMkDl6+MLoo9bybejWcDG/FDB+DwwYDKPOWQzNdPCrrY1pMG5VuurMqJqOADbTMUqDHzdbBw37Kt1s7LtARdMHzEhJX8C6xQyXYcjahbkT3uGGEz2wBPFYQXjm98OIz2oG/RF91djBEu/8+ZfKLX9L1/y+LFQ6e1E4EWASa3NsgOQ3WA+DosSBkOEoeFV9WOw57lpBcegYly1wGwEYPw1Kavr/bLLEa/rb/y9vAC8CNqp6un5mYXE0EX1pXTjAKojXP0m4BtN+Wy1wdaWOnVDqzgHSsSkrCpfAyztbzCK1ubrAMlLeoRE+RosnxcBJsuViTmFbFoxMhv3ynEy52m+zgjgOC3A9UsYAjeolwcPGG+6G47F13tW5mYT0m0nAnMLupeaksfeR9MV0XnmakAed+Pzc1S3VlwpnBwFBugADOABo6q1PAx5u4cY3AAzsPzyCDBZboDECFmkZkduxr2UIpCcZMGVUYrFC6fAJVdmy2zUx3TLzXkjcDNzcGs9D1SU10Gsdpkue+C4NsP7xq/SWxcwqDYaNqoh65fxxsQRUCpEcEovchO9hBypUa1NwPYPenrIft0ZWG75ABgXdOblbwIZpwls3cJQu/SXVC0fgHMyeKg3yI1Pf38cW3kz320TLl02yh/y6rAfv/0tsxGY9QzxK/k8Y7CbBUNeBFz7zxecoYGBrlfeQqXhA2D8tiFtmY8bimfUbLKOb2j2gEkZk6+24yFTO7zJbOSkHjSD+WgUrNGgzci+DHL9psCpbW5GHM3Kbkc7xxClTTWLlrsyhwDz+XxvOQgjKPU+o7q4qGMabk7TSySyNfRB+TxV8ylwznGwytWPcni9KVC1vjddx/0UXnu3btSDw8Cl1hkA418PnTH+JxWJYNSJo4rxaW+XrLp5Y87bXcmqDFySlew+AvCoOnPTUZXbTZNym5f0gNIdVzYFmS/r9xXV112QQz1DEvldUCddahGYjXYDNl/8LqVc/W6IwZP1zOYdYB7EG1OoiNWX8We312Pw4zyYxmcDZpAlXU6lUJwnzzUZ8W0DtrbYmZIzuHw+1DKdIshUPd40bSnaDIgNYELAdFmjdD0vvPWDJKDNzIBwelA2XhjtNVBDDx1tJ/lNqUijrOZ2s2k6viCFQRTzJE+q7Ji3C9isPIBhEJ4bjkmeT5PTHVlz7UlM36F2vpve7q4/Fmz81r4Pe+kQwDfCZ5cfACzI99Ozfe4MZQC5ufvrLz3PXrUJcMYZmJigfDAKML3NAUBVZjO6OFt05CaYmY5+mTOnzPItwDhfK5nL29qXsfL1U1KDAJj2RYZjgIm20UP1ySqWVjRegXc33AfxoY47DNIR5YuegzvAzUGoQd7GOh6+SfkonWQNc+MHQBFsrbiXFTU9VTjYq2zUzG3H3TTmJvdNAS75G2svbSphGFqazEeRwy3A1G/4ztkLFMHChw4bz7tNh8C1ClnoqPAQ5PCmoodOpaGf5oFj2UwHFG4EsMbLdtXOLZvly/y4nxu/JgOIzzb4Zq7CwxVw29JlBhOkDqvNfDO/3xebkJvA+fmJoun5LRPUA+aXuW1smmFyXdpdb0xIBRvgHkJqN5KdeqaGjn/q5LodiTIejEvFaWPd2KSs22UOK16wfGPZVjKgWdNBPw4RwtYqFgDnKxM90fXJmCmayYu2HwD52jS7I6J9zEy8aZk+OaiY/31FiszDmbpxeYFfKmjrYwMhvZJhlFFWGPf1qrTxxDkchNlSvS0Ao/zQvPQnsqX9zzY5U8QnHSAeTMqxcFAznafLbkC0pW5vlWaHsrfPDfNyOuJwBNkRNZMNw6gar276IAZmeDRKdxTgCBVrplQBjG+eti7B7Hl3BMQtT2ECZOTzRWkAbTARIj9qAl8Kalq3lGvYuV53y16YL/rN0p7CwYHll0+n+zq+3WrYnYdAWwpkRvKiKFnf15XTZmTkBbiNbpqPXyi9yI+b5Ie31FETE7AXK9j+MCQ4rzPa4wfMtMAZTtMwF28+ANFsYGN/v2XaOO7wvbEDIG6Zni8ShMi808AF12eoTuAXDwAOK31Z4+JQutHQ2F13S+1NOf90jctPx3Ucgnt+L1u+2VDDuCJtM0Htoyfon0vaq8/U5IzyxmMPAdvYp1E1YPRpdQRsOPnB/gKfONz976Bgh9OROu2BOVXDycXY8v1wYBSsqE/xZk18oCNavlHBsMxL0taJfNPgyZEy88psKtfBenqjo80E2wp2ZkL4pmJu9sh1O5q2jusLgXuT4h4xJ7Ysg03T0ZScb/iQSaP2tHuAb3nT75mhw76/7OP4ZvPvleciMjr6zMaKB9yCNzlVt0Yiv2RAZdjXy1Y7el6Ov/j5wmN+s3N15IDeGpw/N7P1xnTz6Xjl6du91l8AnN/dNzyY/j/HCVfksDv0IAAAAABJRU5ErkJggg==\" y=\"-10.226875\"/>\n",
+       "   <g clip-path=\"url(#p0a7f92a9ea)\">\n",
+       "    <image height=\"218\" id=\"image8a612be865\" transform=\"scale(1 -1)translate(0 -218)\" width=\"218\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
+       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\" y=\"-10.226875\"/>\n",
        "   </g>\n",
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@@ -3394,10 +3035,10 @@
        "  </g>\n",
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        " <defs>\n",
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   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "id": "6b8c1825",
    "metadata": {},
    "outputs": [
@@ -3451,7 +3092,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:178: RuntimeWarning: invalid value encountered in true_divide\n"
+      "/home/cdavies/miniconda3/envs/clmm/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:281: RuntimeWarning: invalid value encountered in true_divide\n"
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@@ -3461,7 +3102,7 @@
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   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "id": "e743f1b8",
    "metadata": {},
    "outputs": [
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@@ -3507,9 +3148,9 @@
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\" y=\"-10.226875\"/>\n",
+       "   <g clip-path=\"url(#peede2cfef5)\">\n",
+       "    <image height=\"218\" id=\"image444975c901\" transform=\"scale(1 -1)translate(0 -218)\" width=\"218\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
+       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\" y=\"-10.226875\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
@@ -3517,10 +3158,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"mf5297eb053\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"m92f6455bb7\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#mf5297eb053\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#m92f6455bb7\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -3556,7 +3197,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#mf5297eb053\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#m92f6455bb7\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -3587,7 +3228,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"118.437344\" xlink:href=\"#mf5297eb053\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"118.437344\" xlink:href=\"#m92f6455bb7\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -3628,7 +3269,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#mf5297eb053\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#m92f6455bb7\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -3677,7 +3318,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#mf5297eb053\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#m92f6455bb7\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -3713,7 +3354,7 @@
        "    <g id=\"xtick_6\">\n",
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+       "<svg height=\"252.105pt\" version=\"1.1\" viewBox=\"0 0 313.644187 252.105\" width=\"313.644187pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
        " <metadata>\n",
        "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2022-11-10T14:23:28.294992</dc:date>\n",
+       "    <dc:date>2023-02-24T16:18:04.492171</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -4188,8 +3685,8 @@
        " <g id=\"figure_1\">\n",
        "  <g id=\"patch_1\">\n",
        "   <path d=\"M 0 252.105 \n",
-       "L 316.822312 252.105 \n",
-       "L 316.822312 0 \n",
+       "L 313.644187 252.105 \n",
+       "L 313.644187 0 \n",
        "L 0 0 \n",
        "z\n",
        "\" style=\"fill:none;\"/>\n",
@@ -4203,9 +3700,9 @@
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p003310dfb0)\">\n",
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\" y=\"-10.226875\"/>\n",
+       "   <g clip-path=\"url(#p46a8475070)\">\n",
+       "    <image height=\"218\" id=\"image5b4e0a7882\" transform=\"scale(1 -1)translate(0 -218)\" width=\"218\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
+       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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
@@ -4213,10 +3710,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"m3628116860\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"m7cc8c38bdd\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#m3628116860\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.499844\" xlink:href=\"#m7cc8c38bdd\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -4252,7 +3749,7 @@
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        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"75.968594\" xlink:href=\"#m7cc8c38bdd\" y=\"228.226875\"/>\n",
        "      </g>\n",
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@@ -4283,7 +3780,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"118.437344\" xlink:href=\"#m7cc8c38bdd\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -4324,7 +3821,7 @@
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        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#m3628116860\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"160.906094\" xlink:href=\"#m7cc8c38bdd\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -4373,7 +3870,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#m3628116860\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"203.374844\" xlink:href=\"#m7cc8c38bdd\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -4409,7 +3906,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"245.843594\" xlink:href=\"#m3628116860\" y=\"228.226875\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"245.843594\" xlink:href=\"#m7cc8c38bdd\" y=\"228.226875\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -4455,10 +3952,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L -3.5 0 \n",
-       "\" id=\"m28de52a5a7\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"m2fd7e40a53\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m28de52a5a7\" y=\"10.999219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m2fd7e40a53\" y=\"10.999219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -4471,7 +3968,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m28de52a5a7\" y=\"53.467969\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m2fd7e40a53\" y=\"53.467969\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -4486,7 +3983,7 @@
        "    <g id=\"ytick_3\">\n",
        "     <g id=\"line2d_9\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m28de52a5a7\" y=\"95.936719\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m2fd7e40a53\" y=\"95.936719\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_9\">\n",
@@ -4501,7 +3998,7 @@
        "    <g id=\"ytick_4\">\n",
        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m28de52a5a7\" y=\"138.405469\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m2fd7e40a53\" y=\"138.405469\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_10\">\n",
@@ -4516,7 +4013,7 @@
        "    <g id=\"ytick_5\">\n",
        "     <g id=\"line2d_11\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m28de52a5a7\" y=\"180.874219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m2fd7e40a53\" y=\"180.874219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_11\">\n",
@@ -4531,7 +4028,7 @@
        "    <g id=\"ytick_6\">\n",
        "     <g id=\"line2d_12\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m2fd7e40a53\" y=\"223.342969\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_12\">\n",
@@ -4575,7 +4072,7 @@
        "\" style=\"fill:#ffffff;\"/>\n",
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    "id": "e3d066a0",
    "metadata": {},
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      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:204: RuntimeWarning: invalid value encountered in true_divide\n",
-      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:205: RuntimeWarning: invalid value encountered in true_divide\n"
+      "/home/cdavies/miniconda3/envs/clmm/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:330: RuntimeWarning: invalid value encountered in true_divide\n",
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-    "kappa_radial, gammat_radial = u.getRadial(radius_map,r_bins,\n",
+    "kappa_radial, gammat_radial = u.getRadial(radius_map,r_bins.value,\n",
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    "id": "080ff2f4",
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    "outputs": [
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+       "    <image height=\"218\" id=\"imagef72610e1ad\" transform=\"scale(1 -1)translate(0 -218)\" width=\"182\" x=\"26.925\" xlink:href=\"data:image/png;base64,\n",
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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
@@ -5302,10 +4695,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"m5d568179b9\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"mceb6b8803d\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"30.549\" xlink:href=\"#m5d568179b9\" y=\"224.815219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"30.549\" xlink:href=\"#mceb6b8803d\" y=\"224.815219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -5341,7 +4734,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"66.789\" xlink:href=\"#m5d568179b9\" y=\"224.815219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"66.789\" xlink:href=\"#mceb6b8803d\" y=\"224.815219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -5381,7 +4774,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"103.029\" xlink:href=\"#m5d568179b9\" y=\"224.815219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"103.029\" xlink:href=\"#mceb6b8803d\" y=\"224.815219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -5411,7 +4804,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"139.269\" xlink:href=\"#m5d568179b9\" y=\"224.815219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"139.269\" xlink:href=\"#mceb6b8803d\" y=\"224.815219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -5425,7 +4818,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"175.509\" xlink:href=\"#m5d568179b9\" y=\"224.815219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"175.509\" xlink:href=\"#mceb6b8803d\" y=\"224.815219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -5469,10 +4862,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L -3.5 0 \n",
-       "\" id=\"md378364b3d\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"m24fbe63169\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#md378364b3d\" y=\"10.999219\"/>\n",
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        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -5485,7 +4878,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_7\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#md378364b3d\" y=\"47.239219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#m24fbe63169\" y=\"47.239219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -5498,7 +4891,7 @@
        "    <g id=\"ytick_3\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#md378364b3d\" y=\"83.479219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#m24fbe63169\" y=\"83.479219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -5512,7 +4905,7 @@
        "    <g id=\"ytick_4\">\n",
        "     <g id=\"line2d_9\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#md378364b3d\" y=\"119.719219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#m24fbe63169\" y=\"119.719219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_9\">\n",
@@ -5526,7 +4919,7 @@
        "    <g id=\"ytick_5\">\n",
        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#md378364b3d\" y=\"155.959219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#m24fbe63169\" y=\"155.959219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_10\">\n",
@@ -5540,7 +4933,7 @@
        "    <g id=\"ytick_6\">\n",
        "     <g id=\"line2d_11\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#md378364b3d\" y=\"192.199219\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"26.925\" xlink:href=\"#m24fbe63169\" y=\"192.199219\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_11\">\n",
@@ -5575,7 +4968,7 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
-       "  <clipPath id=\"pea87f4251c\">\n",
+       "  <clipPath id=\"p2c4c283eba\">\n",
        "   <rect height=\"217.44\" width=\"181.2\" x=\"26.925\" y=\"7.375219\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
@@ -5609,7 +5002,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
    "id": "5c6174be",
    "metadata": {},
    "outputs": [],
@@ -5628,7 +5021,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 15,
    "id": "29a26710",
    "metadata": {},
    "outputs": [
@@ -5638,12 +5031,12 @@
        "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n",
        "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
        "  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
-       "<svg height=\"262.19625pt\" version=\"1.1\" viewBox=\"0 0 385.78125 262.19625\" width=\"385.78125pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
+       "<svg height=\"262.19625pt\" version=\"1.1\" viewBox=\"0 0 383.337163 262.19625\" width=\"383.337163pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
        " <metadata>\n",
        "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2022-11-10T14:23:50.295823</dc:date>\n",
+       "    <dc:date>2023-02-24T16:18:28.231147</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -5659,18 +5052,18 @@
        " <g id=\"figure_1\">\n",
        "  <g id=\"patch_1\">\n",
        "   <path d=\"M 0 262.19625 \n",
-       "L 385.78125 262.19625 \n",
-       "L 385.78125 0 \n",
+       "L 383.337163 262.19625 \n",
+       "L 383.337163 0 \n",
        "L 0 0 \n",
        "z\n",
        "\" style=\"fill:none;\"/>\n",
        "  </g>\n",
        "  <g id=\"axes_1\">\n",
        "   <g id=\"patch_2\">\n",
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   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "id": "13660944",
    "metadata": {},
    "outputs": [
@@ -6755,8 +6079,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:204: RuntimeWarning: invalid value encountered in true_divide\n",
-      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:205: RuntimeWarning: invalid value encountered in true_divide\n"
+      "/home/cdavies/miniconda3/envs/clmm/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:330: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/home/cdavies/miniconda3/envs/clmm/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:331: RuntimeWarning: invalid value encountered in true_divide\n"
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     "\n",
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     "\n",
-    "kappa_radial, gammat_radial = u.getRadial(radius_map,r_bins,\n",
+    "kappa_radial, gammat_radial = u.getRadial(radius_map,r_bins.value,\n",
     "                                              angle_map,phi_bins,kappa_map,et_map)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "id": "5e96e118",
+   "execution_count": 17,
+   "id": "1cb19534",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -6847,7 +6171,7 @@
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   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 18,
    "id": "32772d61",
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\" y=\"-22.024007\"/>\n",
+       "   <g clip-path=\"url(#p7e4b157ff0)\">\n",
+       "    <image height=\"148\" id=\"image920440bf1d\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
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        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
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        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"m2fa700b9ed\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"mbcf4f58d91\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.431744\" xlink:href=\"#m2fa700b9ed\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.431744\" xlink:href=\"#mbcf4f58d91\" y=\"170.024007\"/>\n",
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        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"91.129354\" xlink:href=\"#m2fa700b9ed\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"91.129354\" xlink:href=\"#mbcf4f58d91\" y=\"170.024007\"/>\n",
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        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -6983,7 +6307,7 @@
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        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"148.826965\" xlink:href=\"#m2fa700b9ed\" y=\"170.024007\"/>\n",
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        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -7023,10 +6347,10 @@
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        "       <path d=\"M 0 0 \n",
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+       "\" id=\"mf9dc0e7446\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m4dde90a54f\" y=\"169.879763\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#mf9dc0e7446\" y=\"169.879763\"/>\n",
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        "    <g id=\"ytick_2\">\n",
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        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#mf9dc0e7446\" y=\"141.030958\"/>\n",
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        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -7070,7 +6394,7 @@
        "    <g id=\"ytick_3\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m4dde90a54f\" y=\"112.182153\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#mf9dc0e7446\" y=\"112.182153\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -7085,7 +6409,7 @@
        "    <g id=\"ytick_4\">\n",
        "     <g id=\"line2d_7\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m4dde90a54f\" y=\"83.333348\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#mf9dc0e7446\" y=\"83.333348\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -7134,7 +6458,7 @@
        "    <g id=\"ytick_5\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m4dde90a54f\" y=\"54.484543\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#mf9dc0e7446\" y=\"54.484543\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -7149,7 +6473,7 @@
        "    <g id=\"ytick_6\">\n",
        "     <g id=\"line2d_9\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m4dde90a54f\" y=\"25.635738\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#mf9dc0e7446\" y=\"25.635738\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_9\">\n",
@@ -7242,15 +6566,15 @@
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p3d99f1271a)\">\n",
-       "    <image height=\"148\" id=\"image45f2d49768\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"210.534559\" xlink:href=\"data:image/png;base64,\n",
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\" y=\"-22.024007\"/>\n",
+       "   <g clip-path=\"url(#p6e6ea0cc1b)\">\n",
+       "    <image height=\"148\" id=\"image8c539d9b8f\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"210.534559\" xlink:href=\"data:image/png;base64,\n",
+       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y=\"-22.024007\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_3\">\n",
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.678803\" xlink:href=\"#m2fa700b9ed\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.678803\" xlink:href=\"#mbcf4f58d91\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_11\">\n",
@@ -7263,7 +6587,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_11\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"268.376413\" xlink:href=\"#m2fa700b9ed\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"268.376413\" xlink:href=\"#mbcf4f58d91\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_12\">\n",
@@ -7278,7 +6602,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_12\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"326.074023\" xlink:href=\"#m2fa700b9ed\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"326.074023\" xlink:href=\"#mbcf4f58d91\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_13\">\n",
@@ -7295,7 +6619,7 @@
        "    <g id=\"ytick_7\">\n",
        "     <g id=\"line2d_13\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m4dde90a54f\" y=\"169.879763\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#mf9dc0e7446\" y=\"169.879763\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_14\">\n",
@@ -7308,7 +6632,7 @@
        "    <g id=\"ytick_8\">\n",
        "     <g id=\"line2d_14\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m4dde90a54f\" y=\"141.030958\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#mf9dc0e7446\" y=\"141.030958\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_15\">\n",
@@ -7323,7 +6647,7 @@
        "    <g id=\"ytick_9\">\n",
        "     <g id=\"line2d_15\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m4dde90a54f\" y=\"112.182153\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#mf9dc0e7446\" y=\"112.182153\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_16\">\n",
@@ -7338,7 +6662,7 @@
        "    <g id=\"ytick_10\">\n",
        "     <g id=\"line2d_16\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m4dde90a54f\" y=\"83.333348\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#mf9dc0e7446\" y=\"83.333348\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_17\">\n",
@@ -7353,7 +6677,7 @@
        "    <g id=\"ytick_11\">\n",
        "     <g id=\"line2d_17\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m4dde90a54f\" y=\"54.484543\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#mf9dc0e7446\" y=\"54.484543\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_18\">\n",
@@ -7368,7 +6692,7 @@
        "    <g id=\"ytick_12\">\n",
        "     <g id=\"line2d_18\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m4dde90a54f\" y=\"25.635738\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#mf9dc0e7446\" y=\"25.635738\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_19\">\n",
@@ -7452,15 +6776,15 @@
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p97c804777a)\">\n",
-       "    <image height=\"148\" id=\"imagea573e650a1\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"387.781618\" xlink:href=\"data:image/png;base64,\n",
-       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\" y=\"-22.024007\"/>\n",
+       "   <g clip-path=\"url(#p1ab063ae73)\">\n",
+       "    <image height=\"148\" id=\"imageaae94ae8af\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"387.781618\" xlink:href=\"data:image/png;base64,\n",
+       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\" y=\"-199.929462\"/>\n",
+       "   <g clip-path=\"url(#pad47a86341)\">\n",
+       "    <image height=\"148\" id=\"imagee9c0d8e0f8\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
+       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1wA7BLldNu+wGlf9ngh03djUpRuLyEzJSLj2/LE6lpLODXRgl9xmGv6QKhimS9fBm+an7/Afq5K1uzE2BISEoTLGAVCHi+kdSc9NgcbnmRINtokoTteqgOgPJq/rM1mZq5CDSdTVDETKcOpkteLAO1MoDd6GsFgiXp0RrU976AmQKVeICEyY/plKZe5UKxfq42R7GHeq+9K7dGUY56t1VdfJBnKiVCDxM0azvGKYcXV6Kg8WFY1XKYfJ9R6jg3uMUqAva9l647R5QowqS27/RADCo9PjmzgaP1Goe2NUCm/UZNc76ygf3UOXhiFue2pir9eUCVA6sQzI2ztflDdTaVKdUGNTJn4vne3iWn2Z2N6hTp0Y2e4AdTLYcuYcpcLW3ClPYW9wIlb42sbeZMg25aQRp7Ml5YPavnUPUWV47viXHOLBmNhiINKgfqtXeAkd1qBX1UamgeSqB8abYnuWplBkpJs1UiXXnJ81SEqmE8yFPuC96Gshf0bw6dVbnSgRigMVwCFOuioVaa+pqTKFXJQ8SCmxTdZqBxPt8NA6dHK17BKI6eZGAGMosy1QqxI+CBWolhplaAd4CBaH8cIXptoMqOfI0SxlQjCSqUltSsHJqKiVBqgXu/nL9EIwVGsdWlUmO85Opky8TEAMcmtVVe3slTKFYXFUmp0qdOu17dn2p4A5Ilo+cre3UqKs53YGortfn5BUqEFeoDCy7YqbPV0c2OKqVBXZvgSibacEz9wrllCoJ1xqV5Sq7jHWKXNWqXaraQzUchGoPE0hGeMYzXYaM1V3jialkJepzUzSVGjLTwmrV0YXviLqc6+f2y23dCNcUpKpULmg7C7TXugA+WNo4bDWFyL1GA1zdfN4/C7XyFhioqNSQpYJkBOSp/eXAClQuQDmotNhZlCoKZC0qRS5PdbK9Z0r/oYxu/vg4hufVKThFshIBO5hMmZYwh8kUKTqLC3tVGvPTzuZOQNpDhL0aeXBMjWzfH0FUrM1DRA6mTqF8m6mVojMHSwUmz9VqYoGaq1aFCK7np5vtC58grDm0uejV+hg5Z6RE5Qx6gWw+xFKV/Xp5ZQdsPyjsygeTZvPAO6tjBmIsEE1gWkKBiBtIS29x/aNXpr0q6SS6QaHYqY6tB5zNjflJWqflDBy3TA4mD5FfT9D1h2ccjGo1A2tfZtDnDNmpFbwFQmquqkABO6jajARCiqXYKXo3h2SKleyvXQ8a+wPjLWJUJ/taztasTNDZnVcnZ3W+RNDBFCYwLSUvLdRZXFMpVAWSo/w0Wp2B5PORU5+x1oS6zSshmqgQ3BVu9DWp0fTkFBZto1rpcZ+XGUYb9CUGVMAE6zA3PdSsljuocqlEp6CZKkuzvzUErHErt/4QpJiBTQ8YRQGPI/Fu+GUYJeoBmkxZ6dSpWF0L3uVxCQrTojDlpahSUSdVJrW2HPeqlMf8Fx4AqYMIezWqyjVkn/r8PkQzFfIA0bAcDRZTpNdApcf9xAYptxLDqFZlrC84pbIeIPN8HpIqFGOzYC6ELQWFaiHIxmp7/uAEt8NHleqsbp6dujJBCM7qWo9OwhymvJTctAyKFAeLC7Mg/gBIfKBGLlN9DkQeIAVmDxANr1WFGoExkM6gAh4J7nsbRBfYE3hUKJej7JKNSbgNyQjVGxmti968KCVGWrPWpEoPqvWQSqbzf6UdVLnmp1nvrlXBi9XFqCAtsfwoTPlSHpemSjnSHqQ42Ntoex6kID1cMzUyWMzSfLj2lmeg8DFABorBNgPIP6/ry3ujgjDuZZSDeGfGomuHYE1s0NRK7a+8Blev4qw9P8rgQTUSzPYKUClgS6paeeGqUrnrQdlfdfueJNKuq3lQdzJ1os7mWgifwZQuTpWi/Tiri4O9eaDIq9QJSNyW9z22PUQK0H0VegSgChEAdkDZYzQIZnB8ShvrVzMbnKmVt0BgEtRLq2N7C7U8lQtYW0BaM/JC4KUdtK5r7Qub7noF0xsC1ep3sTqDaYnAAFO+BIVo4QITOqAkYp+dorOzannSno+25myvB8kUqj2OVkYFsrMcdARQdc3O4iym+GVBzPC9OAvZnwfYa2wQyFWt9Ect8OrBmsS7bLa36D37tgJUXqzu06ylKlSYfFg3flftjttldqrV1fCtMOVLhDwFZMtMlwLSUmCvQBlMZnsengGkXRAf1Igfg6hZGk5VyAM02pdXHw+PrRvVyZ7H5OWeZhmJPxmwI7ACQjnDRs/cnKmVfUiWDJZevRKoVtMzCLccsaaA2xawLQHbkhWqiJapzPLso3eDwnlvey6IqzLFXpkMpovaXL40mzOgTJW0t4cKuQcphwKK1ZjCXo2aKh1AxNJZWYXglQD5dY/A45XLHjuFanlHWyBC9zo+DbAzsFik2qCVFAIEgTJexPUCZypV7G/NoVnfFpA2Rr5k5BiaIvjeUf2+pk7O7kZ1KjBhicBlgVwi8nNEXgLSU1GmS4HI1GlBhTnHQZUcSL4K3memQY3sNLIJRKOVEcshQGP+GdXnCJ4ZOOM29hj7y/MMCnUHsNda5Flwt3wFyU6tBNdigRbWZ9dSz8LYhHFNEddLxLYGrEtAvkg7qPXglc/mygXdFenYBfEYVZ2WCHlyMD0FpCfNTOmJK0QVpkGhhFF7nR4khcvBE04gMhtz1saDCvEMpgEAU58OmDvwzMBpx7SHK2Yn9RkCdqE1Iel04HrgGkQVhg6YPWAzuM6C+0LYqRUjI5Do7NCiXlZOyMJIC2MVxi2FYn0KlVwZ6SIIS5u4tlMocfmJXfFyiaBlUZgue5jSEyM9qSKli4FUctOC3uICkKMHyamTzevyNaQCE40gAXoHCmdj3D2XnfqM1nUEz0x1KkDueJ7CRYK41gNbIBILw05NDiB7BLAj9XrUBldkBEKxvw2BNVeNzW66fcsRL1vE7RawXqzIWHKM1aPsw4sAKfX5iV2t6bIoTM8L8psF6TkiPQcF6dJ+8qWo0oJmcdXqxOUm6VUpyCFEZmWmQswzJZoDdATPPdUZ1WaEpXv0ouGOew3ldpMzG5vLDrQzyB4F7MweO7Uq7zOwAhHWYoMrBGwWyP3MhVTy1DVHtb41YrtF5JfSrXdZCkwNJpefqjpFVSe5LJA3lwrT9iYgPbMDCr06LQ6kokg5NJB0DnyxsSBTiDQH5aI+DhR+DKAjeGZAHKnNGTQzyPxyXLuD665vADuNqiwTHUL2CGAJqQ0knwA2BQuMFanYnd5iLcjaJuy5tkrALQd8XBdcbxHXp4D8xLUH5nt54n70H2ZQjKCnJ8jzpcH0RmHa3ihM25OqUlOnokwLalFVYlEmg8hUqIBEoYHkVcjA8QAFznfh8ZY12tWj4IzQHMKD+XoAiKtXe/dCoBbRe4AOIBsA03+MjhVsol5j64N7qDbIyFggCLyWXNVnqi0H3FLExzVivUakD0G79SVHAWgKlfTbEFGB6aJW9/yE/PaC7e2C7W3A9oawPTPSE1ShnqAwRVOnYmdRkCOAaCAdQ0RsEOVDgNpyD8+YdUZwXgvNDJgeqP4PNxwAFm+lJ6cnbrbmw7o/3CsUNmCvZgCQXeg1yGxekwfsSL1mcDEYOrWYqg2GEtQX2bAgY6FULTCJhvSP24KX24IPbxak55J3ov47lDIkuQHhEIDLAjw/Qd4+I399wfbVgvVrVabtmbA9A+nZ1KmAdJFmceWnQhQUIg5SrSyEpkDM+h2I1MINnMB5B48HB5gokXvtHjRnwIwXkjtToxlkcS0HcBU33AG7obV0G1ubwWagrSJ13QjZHjCnagWwM7g6sMAKEjIWzrjItctUGYSPacH79YKXDxek54B8cdXyolAioup0uYCenyFvn5G+ecL69YL1m4j1Lak6vSGk5wLSpYC0CPKCpkYxA0HAMescPM7gkKuVGUDMeac+4QCeI3A8NPeA8Qc+DNv47cZtx+M+vm/2nri6WtOKHir/j5k1tgHd9suD2ya4nGXb+XX23C50ZtsFUP237Exitu3qv8f10YPFlBAkY6EbFldSWCXgJS149/KEd+8WbG8i0kJaMU8ZUuwOywJ6foJ89Qbp22fcfnDB+k3A7SvG9hbY3qrFpWcpmUm0xrUUJYpZIQoFmvrYAApc6mgDPJHzDpxRbY6VqAfmDJYZVG2/HgPlf4dvAfvtACC+SNwpU/eLHUj+df+eTsnQf6lA0sHYAJpAVksKDTCFlKbqZWAFEBYIFmxYeMOCd/WOWWsO+O72jN99/4ztrRYjAQDbBqSk6vR0gXz9FulHb3H90RNu3wbcviGsXxG2t1BlehLkJ4FcBLJkYFGIOAg4ZMSYwFwA4Ywl5GpdkXOFidHA8mozV6FzYI5eH4+Jh2SEYwbGDKDZutnviKtEdD29ClLo3uC38SqlHz53r3XL4q3N7RBpO8BA0/lRBploDCEqgGUwkQNMerhIt10kYaGEZ3qPyyUhkOBDvuCXL2/wf35xwfaGdaR+U7vjpyfQN19j+/HXuP74CR9/LeL2LWH9GgrTG0F6zpCLAJcMXhJizAhRIYqcEQs8sfwEzoiUmwJNwPHQMOUpLOfKs+/Gjwd3n3keU5ozePTzHE9rii+ylA+7B8nevA63Q9jZ4vChwgiY2Ad1JyUAeu0o9MDV3iJJfa6dAEEZncBSQjmDdnA90YKFAp4p4Zk+4pn+EPgaeLc+42d/7musX7/V4ua2gUIA/eBbbL/+A3z4C2/w8ceM6w8J6zfA9laQ32bIUwI/JcQlYVkSYsi4xIQYEhbOWEJCJAcUpQpMrAAV6zuA5ShMH8Hhlx8B4gyAWSZ65H1HvyfeKkCzuR3HXqmvlQ/jPtMOLu/dsv8LC8iqVsNODeKnBlsR0+pQtgwsKComwEKs9kcBCwX8Wgh4phVv+X8h/CjjT/7S1/gvv/dbOqp/u4G++Rrrb/4Y7//KG3z/G4zrj4D124z8NoHeJCxPGy6XDZe44XnZcAkJF04VoshFoShj4bRTnDE8276cddXH12b7T/fvRGUODvwZLGfvO2uzjOVbVajDJntFmrXDLzWdWpx32QwYrNOpmYfPP78gV9gWyghIWAiapYiwEOOJIn4zAN+8+X3gN4B//tt/HvlyAV0u2H7nL+Lnf+MNvv9N4PbjBHyz4unNijdPN7y9rHizrHgKGy5sMG1YCkgLZTBpucIDEspn8t+h7y2fA3K4Hx84+I8cp0/93Y+2+JLvAPVA6+4X8+h7DpRv1209OBgGn13dhUtxU+HSM2meacMTbXimjK+Y8A/f/gFe/va/xr/8yT9BevM7+MO/H5F/8oIf/eB7/PDNR3yzvOBtXPHEWwXJgFlIs1mwqTYFqPEzHh2c1x7sL3mQ/1+2+CJnd8E7b7kbuv+yzU5FP//3+236ayNwGd9jLR/kBd9tz/iPv/hL+Nnfyfin/+Df43eefwo9u7AUWGX+bzalOe56d5/jgf2SH/h+j7Sjz/z/q8XroFD+oNxr4wF95PfsIHDP/SV9bL2tS8Lt0onQ5VVCvZjGWoZcrjniJUW8pAXfrxd89/KEd98/Y/v5G3z1PwL+4r99h7/67YY/+rs/wD/7tX+HH3DAVXQy34sQXiRgLRAmUD0f8Oz7tc/Kh6/512ev3dtvs30HALPNH/ljPGqP/DGctfgi8RyMg9fG6zmN287gANBB4Z+PsNhJnQDqaej+lPRNGLcU65kv1xRxTQEvtwXXNeL6siB/HxF/FfH0c8KPfz/jh//5l8Dv/h6Wv/Xb+Df/4a/jt97+DP/42/+A34yMrykgI2OVjBUJN7lhFR3PTBVqm21hn7WcMNE9b1C179i+f3J/ILaLdqAN+7buP7f6TOEeUa0jcJcDns4Y8S1+SE/7Nx99ofrL/fyoPSx+eQ9OU55k4LgDZefc2fTeLXOdkanTfPU8vDUzblvUeeSJsd7KpLqXAHphxO8Zz98Rnn8u+OqnG776vfeg//m/ISmBkuDt70f8qz/4m3j7l2/4e1/9V/wkXPENRzxRxBNQT1JdxYZyAAuKSTJSWZcE9fVk3wkNsiyERA24ug9oULIJfPU9dex0OA4HUCWaU+HfP0vOpzZcCsX3YI3XrOd6jjI5g2PcbgaJ/qPDetvJbn29/KG0n61Y2JYZUlTI4EmZsSbWM4UzY9tYz3JZGXILoBuDXwjhIyF+T7i8A55+mfHmZwnPf/Qe9Mc/R37/PejNG0AEl18CP/3DH+LffvXXsFDCy5vfw0/Ce3zDhGcKpQ7f5ocBbeinnhENHddMkAKXIJFU0DLawTXQ4Na1Pzr3WOf/7VVNIRyP0x7AERaDwEYP9FjNwEj9vzdpC51DFa85nqhMD4p+uD0sts0IjK330JiV+SvT2fl1UmBKZf2WyinndmZwIuRUINoIWBl0Y8Qrga9A/ECIH4HlneDpu4znX2y4/OwD+Ge/Qv7Vd5As4BghAJYPgviLBf/tFz/Gj59+goU25Kc/wq+H9/ghb3gmxkJt7FAr9gw/0zQjF5jssSgYBJkKYAYeyU7NQHMb1eetA9Ar2XB8qIdgqds5NSrb9PAdw7PgHJqzDkn8mLWXl2YgjV/2QHnqcvmxbUaYTHXqcoHH7vFiF2a1i7PqhTDKhVq3AtHGoJXAK4FvhHADwgshvADxg+DyXnB5n3H55YblTz+Cf/EO+bt3yLdV72wVVZHji2B5x3j/p2/xu2//PL6KVzAJbsufYI3v8EPe8LaML2p9KWplvkAWyv6ItIdrASpgFaiyrh1K6dYZPmkAq9v/Tn2yUJ1T5tc3sCYQUdoBpJ91D89C6TA3nd3aLn5MTSDP1Mee+xDtg/MIjofJ4BFAYRG9qq+BlKXAk6n8cLkynYMoEWgj8IoG0xX68wLEj4Llg2B5n3F5tyL+8gX8q+8h77+HvFz13Ltw0fniIuBVED8A/F3En3zzNf7705/DE2/l+zJy+A6JV3zFOu1mgSAOf8z12g+SwQiloKnh3u44YaDp71XAFniAPGToVA7oQavQlMvHZKdKo0JVp3FXZx63bevm8KTDCvxBR00Y8ZpiB8X46G2vX9/A8esMECnrGjTQq/gaeAWcnEmvlymEnAjIpBCVZdpIFWkj0AaEG4FvAK8KUriK2tzHjPh9xvJuRXx3Bb/7CPn+I+R6hWw6lF3njAPgTfT9Hwgv757w0zff4G28VagA4Ib3WHHDMwlWueEtJzwjdtbX72iqS1xgsrnxgGavql51HFPfYQNfaViv+x5Y0CzTW44HqXMZOoZocce4/p7BxhJoik0WRuimYrbtA2XElxTrhjOwDAr9YoMK2TLQrROvQLbelEegFmbXHC/XydTQ0SBCIvAGhSmpKtEKhBXgKxBuCkR8Ef35kLC83xDeX0HfvwAfPkJeXiC3m06m43KNApuhsInC+IGwfQj41ftn/PHyLZ7DWguZNwl4CR/wFd3wljasSFgp19A+5iprHiwAHVypzAHLw7DMCFinYgeQAW3SIjAHrX4mDxtot+1uCGgErvy+QGm63uCLL8XyDCJvV7b+Hjx6RtIeIP8ouWx/BFEiIKFZWwJogyqTgbQCfFNVClcgXgXxY0b4mBA/bAgfVtCHK+jjtcJkk+iISU/eJAKyZlleoRnsA2P9cMEvn5/x0/gtljo/nfAiC37IH7DyCzJuSJSwUgnt4DrT4RyststncAFzwEy1RhUDziEDetAyHodNt78PnPExDinFWjT0QDl47M0zgFLJRTKFCJDSc9M7XihIHiI9sFR+0B4NpA3grYC0qirxTUEKV0F8yQgfM8LLDKYVsm7tnDu77285ApQFvAn4qoE+fQz48OEJv4hlNkG50fYqEWuMWFEq53xDxoaEjAukTEPuwQJGmNrz6QVEgHqWNqMAV2tXArsgbrVF6FlGGb1VttcbaH4b3c5BW9YZPFWFHCRJephyVao5oPG6xYfgEQfZCJDZGKSpEGSAyEASBafB5B8dSKmBxKuCFNaiTjdBeMmILwn8khA+OpiuNwdT2WVUQHKWR0karFcCvxDSx4j3yxOeog4Mz7rHCYxMV9wo4SvWwJ0gWEiQxc/NagnEwzUFC+jgahcTaYe93nCg/I4ZYLb1EWTAY6C1f/U+bPp52rp4S2FQp2OApARrsW0qUKZIDaQKUQYg1EHUwZRVhdTq0KxuNXUShJs9lp+rILwk8LXA9PEGut40L603YF3V6pw6VburF5kFOAnCKggrga+EdGXcrhHvlqeiUrnbWXqbNUZmxjf8gpwTninhqZYLtMTgwfJnT8/A0oPXw+UVysNl6qUHeg8YCiR1/QFk8M/t8zjQutdtcuSgavoZetgUqC04mPYAjUpkKgSzMik9M8EOImSAijJRyS2U3XKagFR+aBO1udXBdBWEW0a4Kkz8soGuK+h6A24rcFtVnTanTtD8pDCxXlVFpFzBrsEbboRUzjL+GBe8j0+4cCqzLnuwrCW+ljG75EoCmkEXAiBtHvwRWP757gxq9HDpgfLKdx8wg8ND1kEB4OjkXt3ePkd7HWig6b/XYItWofYAjTYmBpopkEFUnncQiUFUHk2NMhxIzeJMoRQi7X213CQOqAy+ZoQ19zC93IB1g6wKkqSk99Kr6lRAsktC1wNTbK+ATCvAN0K+MbZbxIfrgku81DylZ6u0Q5FRpsfQDZkIiRKey5DMhYAkCQuVEy8OwPIwjcszuPT7DLWhrn7kp9c0wOx3z1QMmEMGvA402yZuWxhgQq9CgmZjMkDkHg0e5AaP9t70ehBTkJwqaX6Szup4U0vimyBcM/iWwatXplVhKuqEdYVe/MJ9zRLGifTHzhwmkfJZCsCblin4xsg3xrpEfIgXLDbFl7KbpuuGRYirUmUkPBe10m5/s0EDC7U3Z/W9c9Xy2/j3AefqtT/c6GYrnKlY277/TKOatfe1FreNOxXqrExwCpEHqT02W4O3uREkgykVe6t2Jy47SQnkGXxL9YduG7BuVZlgypRyr051v5RQ7ndQVqg4NYXUCjyQV8Z2C3iJC2LInUrVXGXXTw76uxIzgBsSCM9Ixf60Ws4iyF2+ehyscd3DcAGvAsz+nXuQjWpWtyvvizmFpkJCnRrtICqfidy6To1yUyNkgGsAH0BKTZHIH1AHk/7kAtQA020FrZsq0rZpZjJl6tSJND8xN9uroVzaH4DrCFAC6KbX6VzXgJcY8SEuWMoJCUspJ3j7S8zIYICB53KCWUIu/xW1KmDpdXoy6qn4rwBrXH8Gl37Gtm276ZNvk6GV8Z/dR8f5yvJvxbx5azuBSCwn7dUIBlJRpREkO2i9MnmYxD1KD9Qtg9YC05qAdVOYLHyvCtNUnYhrEN8pFOwzCyhT/WxWqkgrI6+MNQZ8DItaX7E/vSDafJwrEyPTimfaoPOiclWrUHamqhXhc8AaXzuCy/7FUb1mgNX7TXc7afIPT3gyNYuSuAvUcGA1JdJ1oxpBHDAerglIqOUBaQfPno8wbcXm1gEmU6YtQbbkrG6uTrp3qVcmq0Npd7Z9hyS1Sk8bQBtBVsa26BXxPqx2AmfSU6aond3SHSgX/JOlC8qA6JQWe2w2qGBVe/oEsMbX99fg+jTAbOtdm3wUrYsRIjbqIOpBIt3xBpI0W8MAktlcB1iCUybpnje7KzlmlVIqyAWsXEGqyrSlAtNWYMqwi4ZNs5ML41Wp/Ov1D0JhqnkqAXklvZLwqveVuXLEEhIWvtQcZT2/3RkqjJKlzP6oVNZ1pmdVK9L9rRPnUgvuwCeDNdvmDLCZPQJuaOcRFbPvAiDW6vVoaWZh3uK6dajlgClIHVCyg8ug4k1auWDN4C2D1qZOnc0VVbLrEtjVU3bqBDS787dy9bZXLtqq9SjqP3fp8UlRqRQD1pDxssZqfRrQ03CWtC4nEOw4JDCescJuyL0cqFUoE+6qInwBsKydATYDBtgDBhyrmIcsklMoD0unRi4fURfE0QXxPUyyy0+mSGp1BpQt9zBhy8CWqjL5AC4pQW+WWNTJN293RZ1osoOA9t36YqtlPZ3Yl1fBFjRPvWyxXrsgUjlDOJUzmQclSMR4phVgFG3SqTEJgguyKlMZHpnaIAAId1df/hywrL3WHq09omKR0kSNxNlatbcDkEaIcg/SqEpVnVYpNtgCOKUeJlqbEiFnzU12oTCR8mg/e7vTb+sKmoeW11tfA0pVWDZC2gLWVXDjjMixnorOdKn21x8IriqFrGEdUGtTlapbVbXSzyfVBuub60XhvixYs/fdA0y3OVaxSBt6dXKK1CnVBCTkFrgbUC10N3WS/rHAxKmAtEmFSVWpwdTlpuzgKkF8qk7F7jpV8qplrXZCpPuDqXa+QUUlMGQTpMC4hYhQLtsTtks5q9idRTzJU3oQDCgbqmkWmMvszlGtjmzwzwKs9nH373+NikVK1NtahYkGq+tB2uWl3HJSqzlJt8yp5SXacnlelitICVRUqVpdSn1msqv3AlN1at+8QEVDTw+oXV8d16NaPjBFze4PQjIgSacpbxvjxgExBASO7XI95SdgfyZ2JkbmtV9J7TOk0pU+Uqt2UdzHwPpcqMb2GhWLNjTSQncL4KcgVaBkn0GyC+K5z0xqJblCpesHmLYEShkovTix5SxdEN+pU2nkAzgXxZptV8oG9ccrcc18VO5jrLehTRywhYzbFvSakqUuFZ1K+avMlT2uLNSgXs5IRuosUK8RMVErYG+DwA6sL61WR+1MxWIdGunKA/dBQm6w2OucmlJ1y5vLS7Z8BpMP4TlXq/NBXHfoYC/U4Kl2ZzD5qSu+yZilBJwIOWuBVkqukvKTM2HbtNen1qch/SXFehmfj84C7C6lHip/nl3ljlCsTy2Q6+tNrVJng3oYGazrv4ANjnd1/ZT7JUbexlCOfXlgB5U4qxtUyamWWZw+P4EpJVBWFSK7Mm/OClNXHpC9Os3sznYM22Ofpeo983xmdGDNlMrCuQRGZlGoSHDljMCxWZ6/tA9lHTkt4307pZIS3EUhu9Syg+BCWU+Fd2oVfGgH/szz1dltg49gi5TQgTRWv3cgufU85qcBKt6kbFdKA0kDOPIAky8PpFStri7b3Q68Oo3NygO15sR1UNhylPB8h6r1Tar/pr6l52dz4bPlqaBnMl+L9d0otksd2lEPQMi5hylrSUFHojVjLdiqYnG5PFIgPTumXm+gqJXmJDxkg8Dj+SpJPoXIt6PtWoYaQdqpk+wUqVlEn6d4kwbZlgtorTdHSXYwVWB8brJLPw9FTLGbTlciTv7yDl4jUzaDabIPqLM9OOtjpKQqdSO9COs1xXIl3wzGUq9k15UTBoVCvihU/m+EypX+nAXa1ZK9WmGiVnrTgWaDeuBfl69eA9WsxSOIpiDN1Cq15VYRt9mQpSeXpcG0ZSBJg6lYHG1Nmbrc5K3uSJ18I9+zc/WniToZVPrdpUBFvWLXPyJS+8otTyXWKcG3Leh9krNexppJwGnpgKqKNYEqUTsXMIFxsbN+y3sSpAvsAB5Sq0/NV58DVfRq0wMlA1j71zh5sDxM0lSqqtUBTMn16Hxu8jdGtLsdnKmT2Z01m7Lid8wkmHcZyn0/+OGYkoMoAUhqnZIYOYgqFeuVYAhqV7ccK1TWutkJXUD342q99aXS+1MLzFW1HlEr+426316frywjvRas2BUmK1R3VMnZW7U9n5dGVcrSw5SkKZML4RUks7bXqhNQ81O/bj8wvGsTsNp+ofrdJQEITqWIwczYSBBYr1Vll020kB6on+7CpJdu7JRqbFROtiTgIhlruZVuPUhekWZqZb/jxAaB+/nqtWpVFara22GpYADIlQX6R/9zAFPJTGTZydQpOavzoAFzdao7v6iTs7s6S/MgiJe9iDpA7HOUV6vB9lSl0FSKoQGdBZwYgRkhh6JQdrOj/pLS17x0wzJHUNVL7tRclaHz06UG9kO1Au7aoK69n69eA1X0GWiWo/ZqJe1xG59LBUjXT2DKTplE+twkube616qTb0Op4LAOBXTFTdsHs4BuoElGy1IByImRWLBRwFruvNld4J7aWN8upAO7oqedAGFXUNFNpD7WsUAqH36iVvWLfSEbfNQCo7euc5iG5VGRKlQTmHJuMPlakw3y1npT7qyulglOquJdM7szyzOlOmn++Gotysb19LEbinKDxxJE81RVKQGzYEuMwBlrCtX2Wo8vg3PsP8CZUvnhmQKRz1VHFnikVlzOhPkcG7ynVi1DHQTynSolC60NKOvJIfUKVWHaHEB5WB5ykw/i9caI1u7Y3bi+LbedIjPACkjwvbxRsbKGcmFbJr3tayJkJhAVlWJGSGp5REH3j8tTQFEv0RtJss4BRjmCh1BdANwIuIg+nllgeKVavdYGz9SqL2yOMMkxTF34fgVM1eqsxtSBJE2dgNepE9DnJwDdLM0zyyv7G0CtmE8tL1M9QVSKYtnJrXZCbEoa0Il0rC8xlwvMhpqlbqe1KRxCZcMuGtaV7nsW+Kha6frX2+AIVRxBajvywOKcMnUwuRBuMMHZXNejs9xkMwe81R2p06z5LzOG766EcJSdpA/hj2apRKAgJUdpQDeVyizYsoBzxpoZ7Kzvlvt5U3pTplChCmx/SJhCVS8KVtjIkArWzAJLh7R91xO1+lQbHNWqhfKpSilIfSlhKAsUZZnBRJaBJjDZFNyd1Q3q1A7+xO6A3u4sP9XJdZMSwlkzuAwkaTmq/ozhXFBVShWKwEzYUiidzN76bpancgC7y6syy12l8pcizGCANkACEmVcSp3KW2AY1Ko7m9r3BOG2+UwbjJxkr0rSYBrz0gjVKUymTAZOBcjNthytblCnQ7sbpHYXvofnR+N4dUdb2aDs5NkAudmezUCgMuhrKgXWC6mlJCACUs56zVASrBRqOL9RC+Z1NoIeoVOognticClMQ64q32G0wPrrBrUK5QTPLxHaq+VBJhYnXwAmr0zeziTvrQ5oZYIHpk5UdXJDLPUMF7RMNZ2tWUDV4Re3Xiyg90Mw43Rh8SHdikFFpag8bpl1X5WeXiJ2A8iasa45AgywSLu1m//uDio/M/JCwE36sG4hPReLNQtMQD8lxqAq++xLqlUcLc5suVs3sbtXweTVp5YCJlaXe4jaFJUBrlm3dbS2Vw4ZkFepwfq0AIouWxE0mFsRWLLoVflYL/2YktpYJkHKgtWsj6QqVL3DJ8mxSgEVtPHKc3qb3QZVDetAUyjRi6FNa1bAw2qlL98P7VqHGi3OW6AP3x6wOzBViFzxstpebmN11d5MuR5Up2nzp0wBve1Vldq/jWw/15DecpOvotfxWbM9Kh81A3b5IrsqjZD2+IhKaYWktz6EvrcX7qvUhTbcugTQxv3qxDvxYR1OkdBBtQvsdR/N1epRG9wrlD0X7HtygnOYHERtjO4gN9kO80HctXvZydvdafHypFxgIHU7sCz7Ht+8hIB6MRUpc9GFnEpxs75EXFWKPVSZS02KS0gvH2KiUvZ8fwp8g0o368P6LFfpWPfnqdWRDcbDvGSq5WpMCv4EJq9EvtY0FinthIIC1VSdxjZemueodfUnwmGpYPf7++W+l+d6dDO4BECpqotTKbEZCVQunV0q6ERmfapQALo8hVJFD8gKz6DUXHtyfbU9Q9frnRU2fZ02R3yfq+5aoO3DT1CrbixPlcV6ekPBsmYp6RSJLPuMPboK1ZCbCjQ1iD9SDR8a7WpOvirO8/V1J2Fve1nzk9954yxOOMjM9ihLO2YCVRECbJwvE+u+IoWJM4FJe30b6b70PT6ETdVKApDRalT2deo1Q7GDCogDTLH2APc9P78sE2C0IHqmVmXHld3ZwIqH4VsegMkXLg1Ab31dvSn3jy6Ij+o0tbvZ0Iq3uwEe8j27e1Vye4+xPMJjOSobTA0gnarkwnmxKyk5S4iRsyBnxlY+jlkfUymCwixwYnu2DPS3270DlV5LoYX1s1x1ZoGqPLZxe5iVGACfoWo9ypYfhCm7zOStz3KTtzqgt7qxHamTg2mnTgC6ssDJaVOPtGp5wD5DGUzcnkvWf66Gc69SWcf77JYjRHpDACIbnlH72YY8hdwuiMolioDRj/sBO6jafWJyV1aoJzO4XHVmgceBXbc5U6v42TB1mclbm++1NZXqrO4RdboHx1kl/BFVcr24mpPQg9W9NtqeaH6i0sM7UykiDehEgo0UILM+pqDAIAK8gXOo9Sk7XrtqOtBBdQFwg6tRlcfuDGR3WcZDCxxfAx5Wq0hd4LZl6eDywbuuG+1tCOGHVnfUXlMqmPTufEGzu8rKA1DtP4vAzzowmKoqjbZXCptS9mOrXTmVSgwiILPaXyIgca7KZNYHwIV0qHpUy2twvQaqfQ/wHlTlyQSqfp82tbLPEXc1piOYbE7TYGndRDmnPodWd6JO99rU7oAhlO+3OR128b9fSu92NgwjAhkgq0MxtX7V8pQQBpWian2JtKSwJr0Ijrc+ZNQ8pQpVLJAzVnGXqn8FVFYA1Q8Wi+1NiqBAvcb6UWDX7fdqZWDFT4bJ9+iGn5nVnbby+kPTVHbhfDKsMr5my2M4F7cn/bK9pdhhVSivTOjXgQ2mUkJgFKVqKiVZywhUgjCRIDGBs2YqOynUVMsrlPX8ZrWp9oFRobJxP310taoaAvV5huxylX23exbY72N9Hrvqt8xhQikp7GDKe3Xqqt3u8Yuqk9nd7mQEtb3utUcsT4blyc/O+iwr+W2sp+dVippK5aJMdlW9nLXgaUVOMPo85RXKDvTDUG3oSgkFqlar4lfkqvJENKx38uDUigFTqHOYdlVwr0wuhHeK5HpyI0xfut2b5vtwG/iuhU0Pk9mdA8imBwu5bSYqBYJaXwEqEdXalH2DWZ7SHp6rSRULzGR3DmN013Y5harYXikr3IPqzAIZKqpereLDMFmtyZcHBpi63HQSxLuywQN2V9VpZndViWYDxg8E8ww9587vK+mfjzmqAuZeM8hqOOeSrwgASwUqMwGldMAuoBMJWHSGwpinqkJZ+YBE85RTJ73QvjSwDqDSqvoGgB/vAXbP5xZoxdD4EEyzrJR61eos7MTq2oF83O66NrO78QzhBwuZs0ZaroHv6QGYW58tDxZoJQRhqQoFB5aAIZy6gE5kuYlbKSGIAhYEaw3pGdugVt7yFuAOVNyWwfX7ZXAN6z5XhapOmFpg/XdKi4cwjaWAUZ3q60NuknNQZup01g7VyV4/C+W6wfnrKMqDAR40VaJyl4mp9VkgF6qzFfReOE1RyiXpnO2hFDr7gM7EINZJeWZ9vqDZweRB+hJQ+bB+L1fZ752oVRzrTBUmV7i8m5uAqdU9qk6PnoSwnzd+Zw7UJ9WgylvtD1D2P10tyqmS5aYOsgwISVMpAoQFkhmZch/QJ9YHYJenqvWJXkQ/EXd38ATOoWoT9WKtqj8KVQJ1wzQBend3C+yxny0gPUwPhPBdb22EyR+rL6BO1e66ksCd1+2fPM1SUscbRsXymWrMUaNqodagSgmB0KtUsUApvT8f0KfWJ4JNWNWp9Pisgr5ZXcoplL9yXperPFTUrA7TWtUJVPa77PlggXEH0wDNFKYxN3l12h3Fc3U6aodFzLE9ErwfVKrZ/CivVCNEM9uDSOsQCWAzFoQHlSItdrbbyektd2fWp+E8DDAJzmxvBOseVAbHWVlhVCe/n+xL7y3PV8EPCpcVkBGmmdXZv3snW91ts8vxjKBMtnm0Sl5/Z1EgXXa2Nz56+yvrqgVmAFRAI7cOTqXcXVBNpSj0vT4YYKzhvMHUlMrG+JLrBc7a41C1soLOJGhhPdQeh23rd7Q+7y3v7GdmdY+0mTo5u5vlp06djuxs1svTjebLr2y9MrWKeVcimNlesbYazkWVSY/dXqUytTKCDkfmOiOBQ0KyKnq2GlXJUyzlBtOEdbDCDNK5VHX3aNf1DKoE6rPUa8N6eR47mI7U6Sg3/X9Up9rqRVmH8bzxPUdwlfKAQiGoE+3Ka9bD6y2vjet1VfIS0GW2rqjVqFJUHnNGDegsOs2ls77gVSrvVGrs+S1IyESuXrXdhcrG/14Nlf0+WC9vyEeHuQm4D5Nvn5udRnUa2yvtrPyi+5uYdVlz1jbLUbUk40CqwzKZdCNGgXOuUlwgrbUpl6nM+row7iAKQZCFkUlv8FjVKQMLp7tQ2RTiT4FqzFVxV2s6gungZIJdu6dOJ727u0Hc2d3sLgnT8T33+q7d+TpdRdy2l7Y8LXKa8thkOFuXScsHXqUy6WcjQNDKCDlzqU2lok6pBvSUuewKnRyXiWrR0yCL5U4NibhClUFYczyAyr4wKlRtUPkOVECnVvFQmcYQ/qjVWXulOu1g8nObztojsww+s3WqhGOQdrZnNuetsVOpYrEi+nIN6Ko0OTOY1PLM+lTpXDAHDm1vXLdQehgqC+d+qGaESidH9BYYD2Gqwyj3YeraK9XpkfLA4eDv2cUyPmH4pQdlMm4HODAUhkPbcxAZPMIlpHeqZZ9Vj4uITXHJSKK1KaC3vtSF8KzwgWpIT+W+xivQhXVAocoFAC7/6DlUWlVPyF2tKklwwzINqjhXJLf8QDtVp09pM3VyVkZj6PZ3SzhrB11qAA/YXwMMftd06tPbXgdPUTAh/fw6M0G6bUXsJFFxc9B5Z326O1TFxjzVKRKwKydYfaqpU3oMqqFWxX4A00EVH8lNDwfxmTp96iDwrB1lpHGb1/5aKZVx3yogQ8lgss1hz86rVAXsTKUUEi0jQKEqtSlvfSzUWZ7PUy2c7xXKlxKAz4HqOFfFChPwOph8e0SdHp0zfu+qKrvtab/dp/T+7NcJSqY5CfI7Nbpje26dlRBmKqXrddnKCLnmp6JYQtX6cukNHuWpCHQ9v6WEdQ/Wl4aqtzxrM5jG9metTgd2V5u/6spsO3K34pjcEX3asux+59Fwy5ijOogsjJPv2aGqEGiuUkRS/ma1jKC2J+W51qaA3vpqMZNIs5TLUwA7uBpMC9IpVBrEWxVd70ODh6Ca1qGm7SiIdxcJ+0LZyZ6OvTV3/5aunRY+P02tdrWo8fUOLEwsrn8N6NfPspZNbyECJDOEch/QC7ze+nKpV+l+wJCjUg3pKAAZTFb4rFdnAZBr0IvlAvwGiz/H7xyquIPpzOpcOwriU3V67dVUXmNZYyD/lJ4dhhwlk21k6Pnd+X377IT+p+QksTdYsVPKSQ4B04AO5M76AICD5jxVJ+7yVMtRqfb8FqSuRuXPplmAz4Iq3oXJtztB/LPa0Qmdn3Ii5+fUnqTsPTSAul89KNNod4KhZLBTrlL0pHOVsp54HgK61GGZAluZO7VTJ2DIUQbT0PP7wlDFu0C8Ioh/9pgdUNXp1O6G/EQzdfrcgqb/Kq6n171+kKP86zvbK6WDVkqgqUpZwKdJQKfO5pr1MYpKDXnKKukG1+bPSrbJeaST9czn70EVwOimuVTLKzvsIat7VJ1ea3efok51my+fn7pf4extrJgD2EFTweoq5EWBaklBn3cwnagUhoCOUpuikqu2MUP5ZdY5mj6kL5y6nl8X0Ot1Hs+h0uOqlXSbqZBrKH/Q6mr7kuo0qXZP72Z+970HQzWz9x/8zsP5T5PlWZmgU6OJ7dGgXs0629nHcDCBLLNROUwa0DVXKTHe+qio0yxPqSr1IT36gI4CHBpU7K8McgSVm6kQIIiH85smcL1anb5Ue82A76zd29aPf83e7sAZw/tMrY5sr7NFP5ZXMlWnUm4bKyMoVGUOOnDX+jYrGwCInKchHchdOQGwa3JmN+5nQzXcQTRC1Syv7tgHrO416nTP7k4vXD8pIUzyU3lx/ug/ShnbO51XjkmvT/r1ddlBU3MUBnBmtjdRMjlSKQGsum5lhApVCehZ5Nj67GRQaYDNQrr1/HYWSLmO+/VFz2Oo/i98MzuVALfBZQAAAABJRU5ErkJggg==\" y=\"-199.929462\"/>\n",
+       "   <g clip-path=\"url(#p71ba537798)\">\n",
+       "    <image height=\"148\" id=\"imagee481b03457\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"210.534559\" xlink:href=\"data:image/png;base64,\n",
+       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\" y=\"-199.929462\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_9\">\n",
        "    <g id=\"xtick_13\">\n",
        "     <g id=\"line2d_37\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.678803\" xlink:href=\"#m2fa700b9ed\" y=\"347.929462\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.678803\" xlink:href=\"#mbcf4f58d91\" y=\"347.929462\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_41\">\n",
@@ -7852,7 +7176,7 @@
        "    <g id=\"xtick_14\">\n",
        "     <g id=\"line2d_38\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"268.376413\" xlink:href=\"#m2fa700b9ed\" y=\"347.929462\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"268.376413\" xlink:href=\"#mbcf4f58d91\" y=\"347.929462\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_42\">\n",
@@ -7867,7 +7191,7 @@
        "    <g id=\"xtick_15\">\n",
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@@ -9119,7 +8380,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 19,
    "id": "38b199f1",
    "metadata": {},
    "outputs": [],
@@ -9132,7 +8393,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 20,
    "id": "c17883c2",
    "metadata": {},
    "outputs": [
@@ -9140,9 +8401,9 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:178: RuntimeWarning: invalid value encountered in true_divide\n",
-      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:204: RuntimeWarning: invalid value encountered in true_divide\n",
-      "/home/cdavies/.local/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:205: RuntimeWarning: invalid value encountered in true_divide\n"
+      "/home/cdavies/miniconda3/envs/clmm/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:281: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/home/cdavies/miniconda3/envs/clmm/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:330: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/home/cdavies/miniconda3/envs/clmm/lib/python3.9/site-packages/clmm-1.4.0-py3.9.egg/clmm/utils.py:331: RuntimeWarning: invalid value encountered in true_divide\n"
      ]
     }
    ],
@@ -9165,13 +8426,13 @@
     "\n",
     "    et_map[j], ex_map[j], radius_map[j], angle_map[j] = u.getTangetial(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
     "\n",
-    "    kappa_radial[j], gammat_radial[j] = u.getRadial(radius_map[j],r_bins,\n",
+    "    kappa_radial[j], gammat_radial[j] = u.getRadial(radius_map[j],r_bins.value,\n",
     "                                                  angle_map[j],phi_bins,kappa_map,et_map[j])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 21,
    "id": "22ba0469",
    "metadata": {},
    "outputs": [
@@ -9186,7 +8447,7 @@
        "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2022-11-10T14:27:07.045933</dc:date>\n",
+       "    <dc:date>2023-02-24T16:21:49.746011</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -9217,9 +8478,9 @@
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p3c87ebd65b)\">\n",
-       "    <image height=\"148\" id=\"imageebe32042ac\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
-       "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\" y=\"-22.024007\"/>\n",
+       "   <g clip-path=\"url(#pb833702f43)\">\n",
+       "    <image height=\"148\" id=\"imagee483c30d24\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
@@ -9227,10 +8488,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
        "L 0 3.5 \n",
-       "\" id=\"m72ce32f50b\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"m1b912daf8f\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.431744\" xlink:href=\"#m72ce32f50b\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.431744\" xlink:href=\"#m1b912daf8f\" y=\"170.024007\"/>\n",
        "      </g>\n",
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        "     <g id=\"text_1\">\n",
@@ -9266,7 +8527,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"91.129354\" xlink:href=\"#m72ce32f50b\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"91.129354\" xlink:href=\"#m1b912daf8f\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -9307,7 +8568,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"148.826965\" xlink:href=\"#m72ce32f50b\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"148.826965\" xlink:href=\"#m1b912daf8f\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -9347,10 +8608,10 @@
        "      <defs>\n",
        "       <path d=\"M 0 0 \n",
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-       "\" id=\"m5f1f9375ae\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
+       "\" id=\"m8a762b09fe\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m5f1f9375ae\" y=\"169.879763\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m8a762b09fe\" y=\"169.879763\"/>\n",
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        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -9363,7 +8624,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m5f1f9375ae\" y=\"141.030958\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m8a762b09fe\" y=\"141.030958\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -9394,7 +8655,7 @@
        "    <g id=\"ytick_3\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m5f1f9375ae\" y=\"112.182153\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m8a762b09fe\" y=\"112.182153\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -9409,7 +8670,7 @@
        "    <g id=\"ytick_4\">\n",
        "     <g id=\"line2d_7\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m5f1f9375ae\" y=\"83.333348\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m8a762b09fe\" y=\"83.333348\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -9458,7 +8719,7 @@
        "    <g id=\"ytick_5\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m5f1f9375ae\" y=\"54.484543\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m8a762b09fe\" y=\"54.484543\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -9473,7 +8734,7 @@
        "    <g id=\"ytick_6\">\n",
        "     <g id=\"line2d_9\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m5f1f9375ae\" y=\"25.635738\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m8a762b09fe\" y=\"25.635738\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_9\">\n",
@@ -9566,15 +8827,15 @@
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p8117d04e4b)\">\n",
-       "    <image height=\"148\" id=\"imageef091b4f47\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"210.534559\" xlink:href=\"data:image/png;base64,\n",
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\" y=\"-22.024007\"/>\n",
+       "   <g clip-path=\"url(#p8691aa39d4)\">\n",
+       "    <image height=\"148\" id=\"image3f29c907d8\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"210.534559\" xlink:href=\"data:image/png;base64,\n",
+       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\" y=\"-22.024007\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_3\">\n",
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.678803\" xlink:href=\"#m72ce32f50b\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.678803\" xlink:href=\"#m1b912daf8f\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_11\">\n",
@@ -9587,7 +8848,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_11\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"268.376413\" xlink:href=\"#m72ce32f50b\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"268.376413\" xlink:href=\"#m1b912daf8f\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_12\">\n",
@@ -9602,7 +8863,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_12\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"326.074023\" xlink:href=\"#m72ce32f50b\" y=\"170.024007\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"326.074023\" xlink:href=\"#m1b912daf8f\" y=\"170.024007\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_13\">\n",
@@ -9619,7 +8880,7 @@
        "    <g id=\"ytick_7\">\n",
        "     <g id=\"line2d_13\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"169.879763\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m8a762b09fe\" y=\"169.879763\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_14\">\n",
@@ -9632,7 +8893,7 @@
        "    <g id=\"ytick_8\">\n",
        "     <g id=\"line2d_14\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"141.030958\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m8a762b09fe\" y=\"141.030958\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_15\">\n",
@@ -9647,7 +8908,7 @@
        "    <g id=\"ytick_9\">\n",
        "     <g id=\"line2d_15\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"112.182153\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m8a762b09fe\" y=\"112.182153\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_16\">\n",
@@ -9662,7 +8923,7 @@
        "    <g id=\"ytick_10\">\n",
        "     <g id=\"line2d_16\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"83.333348\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m8a762b09fe\" y=\"83.333348\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_17\">\n",
@@ -9677,7 +8938,7 @@
        "    <g id=\"ytick_11\">\n",
        "     <g id=\"line2d_17\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"54.484543\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m8a762b09fe\" y=\"54.484543\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_18\">\n",
@@ -9692,7 +8953,7 @@
        "    <g id=\"ytick_12\">\n",
        "     <g id=\"line2d_18\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"25.635738\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m8a762b09fe\" y=\"25.635738\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_19\">\n",
@@ -9776,15 +9037,15 @@
        "z\n",
        "\" style=\"fill:#ffffff;\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p83e4e5e29f)\">\n",
-       "    <image height=\"148\" id=\"image9920c77a7e\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"387.781618\" xlink:href=\"data:image/png;base64,\n",
-       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\" y=\"-22.024007\"/>\n",
+       "   <g clip-path=\"url(#pc56f07faca)\">\n",
+       "    <image height=\"148\" id=\"imagea6e28ff0bb\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"387.781618\" xlink:href=\"data:image/png;base64,\n",
+       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\" y=\"-199.929462\"/>\n",
+       "   <g clip-path=\"url(#p6364a0b477)\">\n",
+       "    <image height=\"148\" id=\"image1eee4aab07\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\n",
+       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y=\"-199.929462\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_7\">\n",
        "    <g id=\"xtick_10\">\n",
        "     <g id=\"line2d_28\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.431744\" xlink:href=\"#m72ce32f50b\" y=\"347.929462\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.431744\" xlink:href=\"#m1b912daf8f\" y=\"347.929462\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_31\">\n",
@@ -9973,7 +9234,7 @@
        "    <g id=\"xtick_11\">\n",
        "     <g id=\"line2d_29\">\n",
        "      <g>\n",
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"148.826965\" xlink:href=\"#m1b912daf8f\" y=\"347.929462\"/>\n",
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@@ -10005,7 +9266,7 @@
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+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m8a762b09fe\" y=\"347.785218\"/>\n",
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@@ -10018,7 +9279,7 @@
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-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m5f1f9375ae\" y=\"318.936413\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m8a762b09fe\" y=\"318.936413\"/>\n",
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@@ -10033,7 +9294,7 @@
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        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m5f1f9375ae\" y=\"290.087608\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m8a762b09fe\" y=\"290.087608\"/>\n",
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@@ -10048,7 +9309,7 @@
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        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m5f1f9375ae\" y=\"261.238802\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m8a762b09fe\" y=\"261.238802\"/>\n",
        "      </g>\n",
        "     </g>\n",
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@@ -10063,7 +9324,7 @@
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        "     <g id=\"line2d_35\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m5f1f9375ae\" y=\"232.389997\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m8a762b09fe\" y=\"232.389997\"/>\n",
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@@ -10078,7 +9339,7 @@
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        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m5f1f9375ae\" y=\"203.541192\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#m8a762b09fe\" y=\"203.541192\"/>\n",
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\" y=\"-199.929462\"/>\n",
+       "   <g clip-path=\"url(#pc28e751bee)\">\n",
+       "    <image height=\"148\" id=\"image9b027b7055\" transform=\"scale(1 -1)translate(0 -148)\" width=\"148\" x=\"210.534559\" xlink:href=\"data:image/png;base64,\n",
+       "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y=\"-199.929462\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_9\">\n",
        "    <g id=\"xtick_13\">\n",
        "     <g id=\"line2d_37\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.678803\" xlink:href=\"#m72ce32f50b\" y=\"347.929462\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.678803\" xlink:href=\"#m1b912daf8f\" y=\"347.929462\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_41\">\n",
@@ -10176,7 +9437,7 @@
        "    <g id=\"xtick_14\">\n",
        "     <g id=\"line2d_38\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"268.376413\" xlink:href=\"#m72ce32f50b\" y=\"347.929462\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"268.376413\" xlink:href=\"#m1b912daf8f\" y=\"347.929462\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_42\">\n",
@@ -10191,7 +9452,7 @@
        "    <g id=\"xtick_15\">\n",
        "     <g id=\"line2d_39\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"326.074023\" xlink:href=\"#m72ce32f50b\" y=\"347.929462\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"326.074023\" xlink:href=\"#m1b912daf8f\" y=\"347.929462\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_43\">\n",
@@ -10208,7 +9469,7 @@
        "    <g id=\"ytick_25\">\n",
        "     <g id=\"line2d_40\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"347.785218\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m8a762b09fe\" y=\"347.785218\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_44\">\n",
@@ -10221,7 +9482,7 @@
        "    <g id=\"ytick_26\">\n",
        "     <g id=\"line2d_41\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"318.936413\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m8a762b09fe\" y=\"318.936413\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_45\">\n",
@@ -10236,7 +9497,7 @@
        "    <g id=\"ytick_27\">\n",
        "     <g id=\"line2d_42\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m5f1f9375ae\" y=\"290.087608\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"210.534559\" xlink:href=\"#m8a762b09fe\" y=\"290.087608\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_46\">\n",
@@ -10251,7 +9512,7 @@
        "    <g id=\"ytick_28\">\n",
        "     <g id=\"line2d_43\">\n",
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+       "   <g clip-path=\"url(#pb1207102dd)\">\n",
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        "   </g>\n",
        "   <g id=\"matplotlib.axis_3\">\n",
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_12\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"226.264943\" xlink:href=\"#mce3ac5229e\" y=\"204.936307\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"226.264943\" xlink:href=\"#m0f34b7a5ad\" y=\"204.936307\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_15\">\n",
@@ -11134,7 +10447,7 @@
        "    <g id=\"xtick_7\">\n",
        "     <g id=\"line2d_13\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"256.701307\" xlink:href=\"#mce3ac5229e\" y=\"204.936307\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"256.701307\" xlink:href=\"#m0f34b7a5ad\" y=\"204.936307\"/>\n",
        "      </g>\n",
        "     </g>\n",
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@@ -11147,7 +10460,7 @@
        "    <g id=\"xtick_8\">\n",
        "     <g id=\"line2d_14\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"287.13767\" xlink:href=\"#mce3ac5229e\" y=\"204.936307\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"287.13767\" xlink:href=\"#m0f34b7a5ad\" y=\"204.936307\"/>\n",
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        "     </g>\n",
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@@ -11161,7 +10474,7 @@
        "    <g id=\"xtick_9\">\n",
        "     <g id=\"line2d_15\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"317.574034\" xlink:href=\"#mce3ac5229e\" y=\"204.936307\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"317.574034\" xlink:href=\"#m0f34b7a5ad\" y=\"204.936307\"/>\n",
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        "     <g id=\"text_18\">\n",
@@ -11175,7 +10488,7 @@
        "    <g id=\"xtick_10\">\n",
        "     <g id=\"line2d_16\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"348.010398\" xlink:href=\"#mce3ac5229e\" y=\"204.936307\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"348.010398\" xlink:href=\"#m0f34b7a5ad\" y=\"204.936307\"/>\n",
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        "     <g id=\"text_19\">\n",
@@ -11197,7 +10510,7 @@
        "    <g id=\"ytick_7\">\n",
        "     <g id=\"line2d_17\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m83c753ef4d\" y=\"201.89267\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m60cd72affd\" y=\"201.89267\"/>\n",
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        "     </g>\n",
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@@ -11210,7 +10523,7 @@
        "    <g id=\"ytick_8\">\n",
        "     <g id=\"line2d_18\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m83c753ef4d\" y=\"171.456307\"/>\n",
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@@ -11223,7 +10536,7 @@
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        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m83c753ef4d\" y=\"141.019943\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m60cd72affd\" y=\"141.019943\"/>\n",
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        "     <g id=\"text_23\">\n",
@@ -11237,7 +10550,7 @@
        "    <g id=\"ytick_10\">\n",
        "     <g id=\"line2d_20\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m83c753ef4d\" y=\"110.58358\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m60cd72affd\" y=\"110.58358\"/>\n",
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        "     </g>\n",
        "     <g id=\"text_24\">\n",
@@ -11251,7 +10564,7 @@
        "    <g id=\"ytick_11\">\n",
        "     <g id=\"line2d_21\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m83c753ef4d\" y=\"80.147216\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m60cd72affd\" y=\"80.147216\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_25\">\n",
@@ -11265,7 +10578,7 @@
        "    <g id=\"ytick_12\">\n",
        "     <g id=\"line2d_22\">\n",
        "      <g>\n",
-       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m83c753ef4d\" y=\"49.710852\"/>\n",
+       "       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"223.221307\" xlink:href=\"#m60cd72affd\" y=\"49.710852\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_26\">\n",
@@ -11356,10 +10669,10 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
-       "  <clipPath id=\"p8091e3bb3f\">\n",
+       "  <clipPath id=\"p06edd6b62c\">\n",
        "   <rect height=\"182.618182\" width=\"152.181818\" x=\"40.603125\" y=\"22.318125\"/>\n",
        "  </clipPath>\n",
-       "  <clipPath id=\"p69fff7663d\">\n",
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        "  </clipPath>\n",
        " </defs>\n",
@@ -11391,7 +10704,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 22,
    "id": "7e458c10",
    "metadata": {},
    "outputs": [
@@ -11401,12 +10714,12 @@
        "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n",
        "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
        "  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
-       "<svg height=\"248.518125pt\" version=\"1.1\" viewBox=\"0 0 378.465625 248.518125\" width=\"378.465625pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
+       "<svg height=\"248.518125pt\" version=\"1.1\" viewBox=\"0 0 375.967025 248.518125\" width=\"375.967025pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
        " <metadata>\n",
        "  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2022-11-10T14:27:07.619307</dc:date>\n",
+       "    <dc:date>2023-02-24T16:21:50.329535</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -11422,18 +10735,18 @@
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        "  <g id=\"patch_1\">\n",
        "   <path d=\"M 0 248.518125 \n",
-       "L 378.465625 248.518125 \n",
-       "L 378.465625 0 \n",
+       "L 375.967025 248.518125 \n",
+       "L 375.967025 0 \n",
        "L 0 0 \n",
        "z\n",
        "\" style=\"fill:none;\"/>\n",
        "  </g>\n",
        "  <g id=\"axes_1\">\n",
        "   <g id=\"patch_2\">\n",
-       "    <path d=\"M 36.465625 224.64 \n",
-       "L 371.265625 224.64 \n",
-       "L 371.265625 7.2 \n",
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From 63a3f52fb6c0adb9cab3939d2692c47ebdad7413 Mon Sep 17 00:00:00 2001
From: AlessandraFumagalli <alessandrafumagalli95@gmail.com>
Date: Thu, 6 Feb 2025 13:27:13 +0100
Subject: [PATCH 11/14] Modifed "model_profile.py" (previous "modelling.py") to
 compute cosmological quantities with pyccl instead of astropy. Updated
 example notebook.

---
 clmm/model_profile.py         |  302 +++++
 examples/demo_modelling.ipynb | 2306 ++++++++++++++++-----------------
 2 files changed, 1446 insertions(+), 1162 deletions(-)
 create mode 100644 clmm/model_profile.py

diff --git a/clmm/model_profile.py b/clmm/model_profile.py
new file mode 100644
index 000000000..ebbf37047
--- /dev/null
+++ b/clmm/model_profile.py
@@ -0,0 +1,302 @@
+import numpy as np
+import pyccl as ccl
+from pyccl import physical_constants as const
+from astropy import units as un
+
+
+class profiles:
+    '''
+    Class for computing shear profiles
+
+    Attributes
+    ----------
+    M: float
+        mass (units: M_sun)
+    c: float
+        concentration
+    z_l: float
+        lens redshift
+    z_s: float
+        source redshift
+    compute_sigma: bool
+        True for computing Sigma (surface density) profiles,
+        False for computing kappa (convergence) profiles
+    '''     
+    
+    def __init__(self,cosmo,M,c,z_l,z_s,compute_sigma=False):
+
+        self.M = M  # M_sun
+        self.c = c
+        self.a_l = 1./(1.+z_l)  # ccl works with scale factor instead of redshift
+        self.a_s = 1./(1.+z_s)
+        self.compute_sigma = compute_sigma
+        
+        # physical constants with units (cosmological)
+        self.const_G = const.GNEWT * (un.Mpc/const.MPC_TO_METER)**3 /(un.M_sun/const.SOLAR_MASS) / un.s**2.  # Mpc^3/Msun/s^2
+        self.const_c = const.CLIGHT * (un.Mpc/const.MPC_TO_METER)/ un.s    # Mpc/s
+
+        # cosmology
+        self.cosmo = cosmo
+        return
+    
+        
+    def get_r_vals(self,nbins,lower_r,upper_r,log=False):
+        '''
+        Create radial bins for profiles
+        
+        Attributes
+        ----------
+        nbins: int
+            number of bins
+        lower_r: float
+            lowest bin value
+        upper_r: float
+            highest bin value
+            
+        Returns
+        ----------
+        r_vals: float or array
+            bin edges in units provided, or kpc if none are provided
+        '''
+        
+        #create r values
+        self.nbins   = nbins
+        self.lower_r = lower_r
+        self.upper_r = upper_r
+        self.log_r_vals = log
+        
+        if self.log_r_vals:
+            if self.lower_r == 0:
+                raise ValueError('log(lower_r) cannot be evaluated for lower_r = 0')
+                
+            r_vals = np.geomspace(self.lower_r,self.upper_r,self.nbins+1)
+            
+        else:
+            r_vals = np.linspace(self.lower_r,self.upper_r,self.nbins+1)
+        
+        #if no units are provided, set units to kpc, otherwise keep input units
+        r_vals *= un.dimensionless_unscaled
+        if r_vals.unit == un.dimensionless_unscaled:
+            r_vals *= un.kpc
+            
+        self.r_vals = r_vals
+        return self.r_vals
+    
+    def kappa_NFW(self,r_vals=None):
+        '''
+        Create radial bins for profiles
+        
+        Attributes
+        ----------
+        r_vals: float or array
+            radial bin values for halo lensing profile
+         cosmo : clmm.Cosmology object
+            CLMM Cosmology object 
+            
+        Returns
+        ----------
+        nfw: float or array
+            If compute_sigma is True, returns the surface density (Sigma) profile,
+            else, returns kappa profiles
+        '''
+        
+        if np.all(r_vals.value) == None:
+            r_vals = self.r_vals
+
+
+        Hz = self.cosmo.h_over_h0(self.a_l) * self.cosmo.cosmo.params.h * 100 * 1/(const.MPC_TO_METER*1e-3) / un.s   # units: 1/s
+        r_200 = (((self.const_G * self.M)/(100. * Hz**2) )**(1./3.))   # units: Mpc
+        r_s   = r_200 * self.c 
+        delta_c = (200./3.) * ( self.c**3 / ( np.log(1+self.c) - ( self.c/(1+self.c) ) ) )
+        
+        x = r_vals/r_s
+        
+        Sigma_crit_coeff = self.const_c**2 / (4. * np.pi * self.const_G)  # units: Msun/Mpc
+        
+        D_s  = self.cosmo.angular_diameter_distance(self.a_s) *un.Mpc
+        D_d  = self.cosmo.angular_diameter_distance(self.a_l) *un.Mpc
+        D_ds = self.cosmo.angular_diameter_distance(self.a_l,self.a_s) *un.Mpc
+        
+        Sigma_crit = Sigma_crit_coeff * D_s / (D_d * D_ds)
+        critical_density = self.cosmo.rho_x(self.a_l, 'critical', is_comoving=False) * un.M_sun/un.Mpc**3 
+        k_s = critical_density * delta_c * r_s
+        
+        coeff = 2.*k_s / (x**2 - 1.)
+        f_internal = 1. - (2./np.lib.scimath.sqrt(1.-x**2)) * np.arctanh(np.lib.scimath.sqrt((1.-x)/(1.+x)))
+    
+        nfw = coeff * f_internal.real
+
+        if self.compute_sigma:
+            return nfw   # units: Msun/Mpc^2
+        else:
+            return nfw / Sigma_crit # units: adimensional
+            
+    def make_grid(self,npix,r_max):
+        '''
+        Make 2D grid centered on origin
+        
+        Attributes
+        ----------
+        npix: int
+            resolution of grid
+        r_max: float
+            width of grid is 2*r_max
+
+        Returns
+        ---------
+        r_2D: array
+           2D grid (side=npix)
+        '''
+        
+        npix *= 1j #imaginary so that ogrid knows to interpret npix as array size
+        y,x = np.ogrid[-r_max:r_max:npix,-r_max:r_max:npix]
+        r_2D = np.hypot(y,x)
+        
+        return r_2D
+
+    def kappa_NFW_2D(self,npix,r_max):
+        '''
+        Create 2D NFW profile on a grid
+        
+        Attributes
+        ----------
+        npix: int
+            resolution of grid
+        r_max: float
+            width of grid is 2*r_max
+
+        Returns
+        ---------
+        kappa_nfw: array
+            NFW profile (Sigma or kappa) for each point of the 2D grid
+        
+        '''
+        
+        self.npix  = npix
+        self.r_max = r_max
+        r_2D = self.make_grid(self.npix,self.r_max)
+        
+        return self.kappa_NFW(r_2D)
+
+
+
+def KaiserSquires(Sigma):
+    '''
+    Kaiser & Squires method for computing shear components
+    
+    Attributes
+    ----------
+    Sigma: array
+        Sigma map
+        
+    Returns
+    ---------
+    e1,e2: arrays
+        shear maps
+    '''
+
+    kappa_tilde = np.fft.fft2(Sigma)
+
+    k = np.fft.fftfreq(kappa_tilde.shape[0])
+
+    oper_1  = - 1./(k[:, None]**2 + k[None, :]**2) * (k[:, None]**2 - k[None, :]**2)
+    oper_2  = - 2./(k[:, None]**2 + k[None, :]**2) * k[:, None]*k[None, :]
+
+    oper_1[0, 0] = -1
+    oper_2[0, 0] = -1
+
+    e1_tilde = oper_1*kappa_tilde
+    e2_tilde = oper_2*kappa_tilde
+
+    e1 = np.fft.ifft2(e1_tilde).real
+    e2 = np.fft.ifft2(e2_tilde).real
+
+    return e1, e2
+
+def getTangential(e1, e2, center, dx=10./1000.):
+    '''
+    Compute tangential shear profiles
+    
+    Attributes
+    ----------
+    e1,e2: arrays
+        shear maps
+    center: array
+        center of the maps
+    dx: float
+        physcial size of a pixel
+        
+    Returns
+    ---------
+    et,ex: arrays
+        tangential and cross shear maps aroud the given center
+    radius, angle: arrays
+        radius and angle maps, used for computing the radial profile
+    '''    
+    
+    n = e1.shape[0]
+
+    xx = np.arange(-n/2, n/2)*dx
+
+    XX, YY = np.meshgrid(xx, xx)
+
+    center_1, center_2 = center
+
+    from_cent_1 = XX - center_1
+    from_cent_2 = YY - center_2
+
+    angle = -np.sign(from_cent_2)*np.arccos(from_cent_1/np.sqrt(from_cent_1**2+from_cent_2**2))
+    radius = np.sqrt(from_cent_1**2+from_cent_2**2)
+
+    angle[np.isnan(angle)] = 0
+
+    et = - e1*np.cos(2*angle) - e2*np.sin(2*angle)
+    ex = + e1*np.sin(2*angle) - e2*np.cos(2*angle)
+
+    return et, ex, radius, angle
+
+def getRadial(radius_map,angle_map,r_bins,phi_bins,kappa_map,et_map):
+    '''
+     Calculate the radial convergence profile from the kappa map 
+     and the radial tangential shear profile from the e_tangential map
+    
+    Attributes
+    ----------
+    radius_map: array
+        radius map
+    angle_map:
+        angle map
+    r_bins: array
+        radial bins 
+    phi_bins: array
+        angular bins
+    kappa_map: array
+        convergence map
+    et_map: array
+        tangential shear map
+        
+    Returns
+    ---------
+    kappa_radial: array
+        radial convergence profile
+    gammat_radial: array
+        radial tangential shear profile
+    '''    
+    
+    _N  = np.zeros((len(r_bins)-1, len(phi_bins)-1))
+    _K  = np.zeros((len(r_bins)-1, len(phi_bins)-1))
+    _GT = np.zeros((len(r_bins)-1, len(phi_bins)-1))
+
+    ii_r   = np.digitize(radius_map, r_bins) - 1
+    ii_phi = np.digitize(angle_map, phi_bins) - 1
+    
+    for i_r, i_phi, kk, gg in zip(ii_r.flatten(), ii_phi.flatten(), kappa_map.flatten(), et_map.flatten()):
+
+        _N[i_r, i_phi] += 1
+        _K[i_r, i_phi] += kk
+        _GT[i_r, i_phi] += gg
+
+    kappa_radial = _K/_N
+    gammat_radial = _GT/_N
+    
+    return kappa_radial,gammat_radial
diff --git a/examples/demo_modelling.ipynb b/examples/demo_modelling.ipynb
index 2035956a2..d7bdc6e2c 100644
--- a/examples/demo_modelling.ipynb
+++ b/examples/demo_modelling.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 36,
    "id": "45308159",
    "metadata": {},
    "outputs": [],
@@ -14,6 +14,7 @@
     "import matplotlib.pyplot as plt\n",
     "import sys\n",
     "from astropy import units as un\n",
+    "import pyccl as ccl\n",
     "import clmm\n",
     "from clmm import Cosmology\n",
     "from clmm.support import mock_data as mock\n",
@@ -21,7 +22,7 @@
     "from clmm.constants import Constants as const\n",
     "\n",
     "# profile modelling package\n",
-    "import clmm.modelling as mod"
+    "import clmm.model_profile as mod"
    ]
   },
   {
@@ -72,12 +73,11 @@
     "c    = 10   #concentration\n",
     "z_l  = 0.5  #lens redshift\n",
     "z_s  = 1.0  #source redshift\n",
-    "Mass = 1E14 * const.SOLAR_MASS.value * un.kg\n",
+    "Mass = 1e14 * un.M_sun\n",
     "\n",
     "# define physical size of grid\n",
-    "units = un.Mpc\n",
-    "r_min = 0 * units\n",
-    "r_max = 50 * units\n",
+    "r_min = 0 * un.Mpc\n",
+    "r_max = 50 * un.Mpc\n",
     "\n",
     "# number of pixels in grid\n",
     "npix = 512\n",
@@ -92,7 +92,7 @@
     "# define radial and angular bins\n",
     "N_r_bins   = 30\n",
     "N_phi_bins = 25\n",
-    "r_bins = np.insert(np.logspace(-2, np.log10(r_max.value), N_r_bins), 0, r_min.value) * units\n",
+    "r_bins   = np.insert(np.logspace(-2, np.log10(r_max.value), N_r_bins), 0, r_min.value) * un.Mpc\n",
     "phi_bins = np.linspace(-np.pi, np.pi+0.01, num=N_phi_bins+1)"
    ]
   },
@@ -119,8 +119,11 @@
     }
    ],
    "source": [
+    "# set cosmology\n",
+    "cosmo = ccl.Cosmology(Omega_c=0.25, Omega_b = 0.05, h=0.7, sigma8=0.8, n_s=0.96)\n",
+    "\n",
     "# lensing_map has the option to return either Sigma map or the convergence map\n",
-    "lensing_map = mod.profiles(Mass, c, z_l, z_s, sig=False) \n",
+    "lensing_map = mod.profiles(cosmo, Mass, c, z_l, z_s, compute_sigma=False) \n",
     "\n",
     "# make map\n",
     "kappa_map = lensing_map.kappa_NFW_2D(npix,r_max) "
@@ -143,7 +146,7 @@
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        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2025-02-04T16:11:01.954245</dc:date>\n",
+       "    <dc:date>2025-02-06T12:27:04.266890</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -174,20 +177,20 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p09d1bbdc89)\">\n",
+       "   <g clip-path=\"url(#p583cec632c)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
-       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F/FXL5WO7OPgZqVhug9P8pwIil0aLDj4njftIObhpp/EridspPCRw30HQEHa1EnCdXhyZHymc/Mncmc2SdPAzgUcnCd0F9Yo4IPKCcDjQWUS6MVLSuPv7hxI/pXD7d76fE5G+eEzK7sKV3sX6La+vdP5E5jkVS65Ie9YrN8EBz7JA5BxoceA1tVYplcZVYDluL376mfqS9VcK9wj8ELe9ytC4tSZN++/W7XZK7zJfiEJC/6paXJmbx+ST+TEmT8WSwO1U3iK9T9xLc2JOkUuesdKTnDQe+519cNOXxPffaY/YbdmfBO68UIRSuTJC1Jrotf2rV/UtdMdNh8zN/d1kbpbpk2fGyUBJ9wFhJn1hqStyrlMPpXJR3VSvVVKXlzJf3D046atTlPXlSF0bkYZSeeCxHcF23cem9VGv6FVtWV2pT+ViyfSUzN2axdxPn78PViy+VP5EQqXrFbyQlCXz75PLnIkc+LlTq6QeFwhVKu5MlwuJewXuJHIdHZIipWkTNe371qoOoW//JzoW4aTzL5mb58BO69kfpHwtzS4HPYEYIPJCcDjQGaTEtMPYhbGIrtO4e1s3nWdKXC+LI/RtnUcyD/05NNHm8S1tK60sgStS60q0WOmcKC5zonMKd/+f25WXnorIWPg44FkOiLw3vfr6HrWXPUuF6LsX/7q9R+LL4nxPH4Er+kg9crDzM1FlF+lKm9BpJU3L3qOv3zJ/B6TjVizmseZ05SWo/PY9vN45e2lOQOTAS4laxduNh/7vS+Mhib/2n78+Aj/uu1A4lev9h1pvHfku8SM507Kl8zeRWrYYfpK5NW5vxWLf5iqVu9ypVwDYgcilUPpA59fyI+8MbtYq0eU70g5VKlGJL9Z9l03mh9iVZxyrSeOK1KJJrZv01ao/3n0T0Yv8Mjdd+M5XxZKTykvUKw9rExzwHAeIfHRqXbI2FV8XfoVduZhO3CNxvWw/MwLXy3bf7f9mnfu/mohe24FOterdoZvQaSWitzVMW+ZKES16+715UQlVLO5jdlI5ALWYT+SYQ16GnHcIuWl8W8Cers8HNr0SX+yfm5rFvhjWvsh1nzW4Eql1T5u7wBXtzYu57Zu2g560kFpX0nsF714hUS9E6q3PLzyBVN4tATM+4FmFCTv7+UQOLlNxVk2TUqskrPPArVTsasWR+PpaNnH/WA6B6x/0SeemYiHaZhsaiWsi9XP/flGkfq6klKKF1rPMzXQVrT4zWXypPJS4Qz9PqVcCXL4YIP1PCUQO0sl9N3N1kNP9nXtw1E7lio7vyU7fPxbSr03i6w91fL+J3VnFan0pouUn7YZfiH6uW3dOtE1RVNvv1L7u7cXNub4KUViarlBzBTthqgT3gcgLwHoOeQqpBzqLrCtQqxh8afw4+EmfKmVRh8Q3gW8iX1+0/ez1SeVEdKTx5a1JvdX2kNVWoSy0yVwfBxhpm4K4qK1vWfR3KjfZfU//0YOeJZ6zSgc8e4O55GWAyEFxov14+E5fp+q7afyYnXJ05XT04+sPResPovef1C53+vTltB3gVCuR/qm2/vsPTaY80ftZmdsnBxGpRZPWypw59J3Kib7P5oyR05MDcAOIvCdSD7yWTulu5eI+LXsaNwn+EPhiBP6R+PrnTeLrn0zNsq9i3QSu/9BbpXIc3tyEvej9trvE1Upb7eKm4YW2dF5rRgqm/IEbQOQD8HgOeSnuHOh0pyfa39tTD+2TfY5+3NQoH4m//6zo/QsdQtevfXHvrRNf/q7o9TvRR+L6mM2iV/NWn/ZpiVYSN/XK6XR8z/e+xxc74NmZYu8Q0Ol3BSIH97kzu8Xi9Lmb+/fu5WfNrJPPwU6rJzcJ3fTiP4jev+xf/0D0/kWT/rFJSv1U9PpdbVPRzeyV93Y//d7rm/0AqVJ6X9d25fJj6uExJvXp0PfZK3pR2zRE9zGnShKzTcADIHLwnNjZnsH7xFP6kcKJjlqFyAidjnnietkObJo6Zf3zJvGff13p/dc3qX98b7NQfnuR/vVFRMsm8vcm3u3Apz5NVzyJW9ljcnpy32PKnRqIJAsKAJFLQPqsGIP7QRG5KPokdyPexfo6Urmm91/f9Jf/9jf6l3/+TyIi+vf/+Cf6G/2F1B+Klj8+/blezi8M6hinmWKYmZJDJwZJhUkFBOJA5EAeVt1i/n8cBH0R6T9pUv/4pn/55/+k//2v/4+IiP7P//+f9G+//kL6x+uY8UL2/dV52QBIAiIH47GfxUlE9HbPCgJgQCByIA8zWUR//r/NE9+mGKqfivRvL/r3//gn+r/0P4hoq1b0by9S+zzy7fM3rfvr87IBkARELoFVj9GTr/ozR/xOT673ZbzUIeLTaff7FMPX74r0ry/6G/2F/u3XX7a7/vai168vev2uaPlJh8zNtVfMso5xaro3i8R8gPMovfIoj2NwIHLwnG3itfMzHZe13udxB36ntLlGuLKkul+GdnelEfHy1qR/qu1kn79vUwyJFlJ/KNI/tonkx/TD34hevxMt+4lBy1sfyzHJXNnu0ucxReV+JX7f7zFjBRQAIgf3uZL1xW3Vup8WT/RJ2lqTtgSv9HGm/HYavVbH6faf+eDKSuMfGW+zU/ZT9K3fL3+nTyp/77WM1vty9S50fQhdOf5VRshWWlW+5JqT6DGHHDwAIh8AvX+UWHdCFVBM+O6VBO3v1/2kHG19OPKyfyjEqrZL0ar9ci5/mISvD7mfT9HfZW6S+N+JXn9oWozM98va0i51cx2VI4W711UJfe97fKHnigHFrvuCdxZdgch74qskJFC6s3dFvxLRy1mf+pxOr9Q2t1mt5lK0RPa1U7akrcl79cM9ib+M0H9qWn5+0vhWs+zyNp386bFTusTvwETwQBYQOSjO6R3CuqZdAfH4IGRL2nsSV+YaJ+YzNvePXlP7iTvbpWiJzLVT9GtP5J7rkW+XsSVa3pvE1dsS+PuTxo+6Za90TDI/1SqpErcuM4srH4IaQOQF0KuWfU3ymGxLp2975gptctXmmuNEH4HvtQod/263Uas+PgBZ/VyJaKGF9H4p2n155rT7/YzNbblWp77uMjdJ/L0t65PKrTRu1yrGx04i/yT4SjNWYssTfC1yIsK1yAsBkYN0cqsgtzK56sqJyKTqUCrXmrY0TnvFssuctN4uUKjpuABW+KPe9N6J70n85/qpVN6f5O2m8dM4c2ew5CZxdM4gA4h8Ri5mm2QdPD2ku0s+94CnOw1xT+xfqZzW/WMg9rsRbZ+xqRVpvX4+aGKl03VYbD5zz7WVzK0Ubn2v3npLu1YaV6HEHZL01YFOI+sMyV9WM6hupmQ+kUs9wMiNi8ol2pM7JwapVTvS3dM4mfniK+nN7tun+5h1kPUSoIlo2SoucyGs4xio+T2ZekUfB0vNtMMviR9d+epP5aYzX52ffR0czejHa9UMwuuXbCZ8NzOfyGcj9WBjLdwphUTXc8+N6JXaEvGyVyxvInrRSeZ7ND8+nm37UPq9H3dfaFb9qViMhK1ZKieJv/V56qEZf4ps3doFKRlUBiKXQk4CvrX8xAOesbM4Y/VKLJWTddDz+D3R8cEOplpZli+Za7XXMPvHs6ll+1CILY27Fci+LnueuH0CkCvxvVo5VSpuGo8d5PQl4ZRaxU6UFQ90dnuHAIoDkQMvSS8MqS8uV6l8/9mXzM3PySPzRW+duflcTU3nWS7uOuzl7QcxjcCPpG6L25W4jkjcXYcnjZeQJqYughAQeW96dfYXBzwfk5PKQ+OwUvtJ5kptnfn+/SHxRTnduC/t7suzBW5VKKYT/5J4TLS5abwWvUQ/YSfNDYi8EKznkpfoyXPrlePHCancEpC3YnFlvuhduGrvwvXnbM/9I9liHPI26/6StkfisUrFfg5S0niJWiUVxgc6MYe8HBA5+OAIv0S9El2H6aqXs9CvZE5vOgtcW/Je9ktuXc1XNycV+QRubnclcfs5OP0/U553ahXGggbtqSvy2m/fZ6P0Ac8nf5+Mg57BVH5MT7QqlpDM3/vt98/9/FQt+iN0IjJGD6Xyk6jNv16p6/NtfBJ3K5VYGs89yJlLZq2CA52NqVx7zZnIMZf8HqEXktgLTKwrtysWty/X+lvmRJ90bl4clLISOn1eCC7PICV/AjdjdoSt3NRtS/x034SZKr7fpf4cxJm0r59T5Nxo8cKS2pPfqVdsUrtyt2KxZW7hlfmRzj/33dK0SePmSoh+vKmcyJvCtzFEkrivUrmaqfI0PafWKi3ql0nFyQ2IvCAcDnhWr1dCBz19yfuqYjEyP/3MX7MQRYRO+7ptqac8bjNu+/9uCjc/i0lc67DEU9P4k4OcpWuVBuBAZ1kgcmmUvhqhdx2FUvlpmc9kThRI58fyj5VfPz++Xtv5V7np3Px7R+I2rdL4EyBZcUDkM1HqdP2UVB6oWE74Dn5GahYiTzp370e0JfUUXFEThVO4eXyB+0UF7TvAWSqNh8CslqmAyLlQsCcvk6AzUvndisWs20jHm8zVWdY76v0Z85fUUx+zWZav706R+Pot6EeVytcQE9J4z1qFWz/ObTwNqS/y3A62FZJnrjypV2qk8hCnxB2ReWxsZt90h+zp0PcVkb4Y19cHJecK3IzVuW9U4ikC5ZDGUauUp8ExCSTywnA44HmLO6k8p2Kxb+Pry4nOnbmvaiHy1i0udlr3Ps7Yz3z9dkmJJ1YqNdI4F3CgszwQOSda1Su1Lm2bIvNjDIGaxZW5TY7QfetMmQ4YEzhRmsSTll2pBoik8aFrlcmByKVSY/bK01QeG6Pv4KclcyL6ns1CdC10oqSUfowhNE7f7XwCt36uryQd+v3F+rulcSRlscwt8ko9OZd6pVYqT65Yvn5nyZyI3GuXB6sWIr/Qj9sEBPR1VmhsZklgBopH4GasX8tNqVPc211JPIdWafwB1WqVyd8hzC1yjuS8uHRK5dfLSJ1yaHXmRP6qhSgsdGcmy4F9DZfQGK5+HhD49l9fj554YDNXOBzT+OTS5EgbkXOduTIBxVJ5bsUSm5Lok7l1u1PVYm6//SAtoaeILlizJAjcjPX4RUTisV78TqUSQkAan5JGzz0SOfgm8YU3W+ZE8dkszu2ShG6wr9uSQ0LiDQrcjN13v9jtPL9Pli2kDDxA5Bx78sL1yq1UnlixZMnc/b0rcyJvig8KffvhZ2xP8AjyOyFH0nVpiedUKk/TeKNaBf14PSBykEcNmRP5hX6amaJOUvJK3SZnHrnzWE5cSTn39nclDkAEoac2yuBRAslJGQnriSazkDhuJMDgmC6E9rUu3+2t+2itT19faO3/+rpZYDnO+rxjeihxLwX/FlOkcUBELRM5DnjyJqdi8eA/5T4hmROlpXP3Pvb9qNABveAsl0yB++7juc3jXhzJnXet0vB4BqoVomo9+WNaduXxO97ry33jCsnZndVC9C103/1cUo9LXCVEnyC8NchFCg+s63EvfgGnNA7qA5FXhsvJQYaiJwndlTnRdTrfFrb9qzwvBET+F7kadVaKwEP3fyLxGIKmG6JWqQ9EPhIlThDKrVgCMiei7wOgRGnp/Ot2nlkq9v19BE9IShRm6un8oWXmVCk1jlFcMYJc8S7hoG2fwCwpnOC6UWSfCfjwwGf8joF1+sfoT54ZIgxdhCpw4PJrmb6v6H0iyw6Oh5fEi1cqRHz3Dc40dh0SeQO41StEDyqWjGQeXE9qOrdv697ejMXH1XGA1J0sem2WNIFvqysk8Qu4VSpEqFVaAZHbjHDQk6huxUJURuahccY68JjU3fHdJVfeF/crKvEelQrXNM51XJ2AyBvxOJVXeJG5nMVyV+ZEab05kT+dH3cKpHT7fja5z2+q1FoIfLtTZD0FKpVcHsoSabwd7UWO+eRtSEzlVWQeuV80nRPFhU4UfzErKY4riUXWxVbiEGsbOlRcDHuEzlR8y/Y4oVQ48EmUIILCAgqejUkUPqh43Dnj4GUOqcuNjC/+uIRJnHMaR63yBaoVkMaTZE4UTOdEnrqFKKMPb7BTX0jp1uUPPne+f18AdvokcoZH11shNpUTXafKm1KKJlmiTwpuWQ0krPN63HWeL3v9SSCNt6OT25DIfXCdvWKoNIsl6RT+q7M/b6Zzs36iQEI/llHgIGfKMiM8qqK2BTy7f8oYjmUNMksFRIHIO9BlXjkXmZv7E10KnehC6sfy6qegx+9YPgt6vAzOBzcxU6UP/WIn93qFezK5M75WNcu2kDRpJRzMu6wwKpG87oTHkfx8JIwpiTtCHXGbb0lHpyGRd6JIKq9YARVJ5tuCrqebXiR0e0w2t67kmLH8S1IPRhYQ+LYY3t0z0ng/IPIYlbtyzhULUYbMia6rFqJiQrfH14VSAs9YVtZjHbFS4Z7GO9P3iB73ekUCFSsWopy38on9cKrcUuqKluSMKedxJlBd4pDkczq7DIn8Cgmp/M4YSydzovREnZrQ7WUacq6X/oQ7LyIlX/SORfKXONJ4fyDyUWggc6LUWSQJ3fm2UNoXmjSGY9kuT+X+NPlnybZSH44kPjX9RS7h2isSUvldMq+UWDydbwv9fH9nW+hRwdQ6MEqNJF4IpHHqXqsQ9e7IwUGRHeLuRl/6hJjTsjO77tQPjujBnbFlPv5mEpdQqYBk+idyKXA/29Nwd5w3kjlRxhTAzBkp+0o+3/d613b3BSXzXcKtGTgdJd4EKeNkAA+RS6hXGlCsYmkkc6KMquVYxw2hbyv6/lnpbabEu4AbNY9EiSON7zB558hD5FJokMqlypwo8wSdu0I/r/j+fUvTSuBEc0gcaTwLPl0Bp51yFJ505jd21nvJktl88Vxujv92Ch+9TpEEI2chkeciKZVvC7s/3lbpnOgsw1Zzxe/y4IWneQonKipxpHGe8BI5uvIDyTIneiB0on4nAYUo8I7h0eUEZpK4FBilcSJuIpdCoxks0mVO9FDox/ornASUs64HPL4ezGwSRxq/BUR+lxllTtRX6Kfx8N7huwqcCBKfDH5lJLO3LMPxdGd5uFP3urZ4K4o8PkYSBx4Ybr9I5E+QmMq3BT4b98N0TnROrKWvK96aYi9MPc/uDS4OaVwC/BI5EctXvCCNNsDiO1SJcRf6QOSenwJ0l6JjLvXB0pB4fZhuozxFDrywlDlR0Ys2cZZ6lbGVeu6kShwUgW+1ImkqYsPrsFSpWYiej79A3eLiE2arGqb6CwlTgW+LbChxpPEi8BW5NCTLfFtomfFXELrNlWBTRd/vY+IKrhcSBzu8RS4plTeGtcyJqgs9BMdKhojKXzNcusSlwXW72uEtcmk0vtRtNZkTlRc6UXOpd6eGGCul2OYSRxovCv+DncxfCb9ovIFW2wFrPI5SszO4U+txQuJ9EOAgJPIBqPZRcaXTuWHElF5ThhXFB4mPAf9ETiTiFfFEh4216g5Z8/GY9CoxqbcY+0gSl4gQ9yCR16LDR8NV/RDnWuncxhULt7Q+0IyOLhJHGq+GHJFLnMEymsy3FWz/tnhcPtm0knuvtNpAdpB4IkLSOJEkkUtlRJlvK+nzYdQ5EnKfA+5VAiQObiJL5BJTeSfMDjtMOr8Dd3EbRhW4ZASlcSJpIpdKr/RKDdO5gavUudEwpXaVONJ4E+TtdcJeKQ86btDNT7vGzhum8fMDid9AoGPkiZxI5BNNRPPIfFuh3B25Bh2eD0j8BkLdgmqlNZ1rFqLKvfn3Sj/fz1a7dJJZ9z5cqsQFI3fPEvrKSUTdN/RuO7pJpSPv6J0fIyT+AMFOQSLvRcdkvq2+Qzo/D+DzvfSkzkBe3QW+DaL3CKZFtsilT0fsLPNtCA1mtVwP4vx/7mJnJixIvACC0ziRdJETQeZFhtA5nbv4pNDrOWIsKBYCJ2L9HCUhXOJEI4h8BBjIfBsGM6HbpMoi9XkULB82AicS/TyOxBgil57KidjInIhJ3XKXwcUCiRdmgDROJHnWissIfxBGO4ZeNS9pTA67vwejbfU2IzhjZ4xEPhKMkjkR87plAljJ2zCCxAeDjzFKMMorLMMdhV0iHBy2zzfDbfMWo7hiZyyRE43zB2K6w7AVzCCwfn6ZbpPZjOIIi/FETjTOH4rxjsNaOAJh/3wy3hazGMUNDujIucP8mt+2fNCj58Fa3IZRBD4444p8hCmJNswOgvqA1K8RIW/DaBIfNI0TjVqtGEb7wwnasdhXBY0R93wI2taSGM0FDuMmcgOSeVdcec2S1EVJ22Y0gRMNL3GiGUQ+Isx78xgj1y9i5W0YUeKTMIfIR0vlBmHp3MUnPilyFy9tl1ElPkEaJ5pF5ERjy5xItNBtOMp9OGnbjCpwomkkTjSTyInGlTmR+HQe40qkT0U/tKhjQOLDMJfIicaXOdGwQg8xrYjvMrLAiaaTONHo0w9nZfQdFdwH28aQzJfIicZO5YZJ0zkIMIvAJ0zjRDMn8ln+4LPswCDMLNvALPu0hzkTuWGGZE6EdD4rswicaGqJE80ucqJ5ZE4Eoc/CTAInml7iRBD5xkwyJ4LQR2U2gRNB4jsQuWE2mRNB6KMwo8CJIHELiNxmRpkTQehSmVXgRJC4A0TuMqvMiSB0KcwscCJI3ANE7mNmmRNB6FyZXeBEkHgAiDzE7DInOosDUu8D5P0BEg8CkceAzD8gpbcFAj8DiUeByK+AzM8gpdcD8vYDiV8CkacAmftBSn8O5B0HEk8CIk8FMg/jyghijwN5pwGJJwOR5wCZp4H65RvIOw9IPAuIPBfIPI9Z0zrEfR9IPBuI/A6Q+X18gpMud0i7HJD4LSDyu0Dm5ZAkd0i7HpD4bSDyJ5gND0Ivz5Uwa4keom4PBP4YiLwESOftgXDHABIvAtP3rwLBBglAHthnigGRlwQbJgBpYF8pCqqV0qA3ByAMBF4FJPJaYIMF4Az2iWpA5DXBhgvABvaFqqBaqQ2qFjAzEHgTkMhbgQ0azAa2+WZA5C3Bhg1mAdt6U1CttAZVCxgZCLwLSOS9wAYPRgPbdDeQyHuCdA5GAALvDhI5B7AjAKlg22UBEjkXkM6BJCBwVkDk3IDQAWcgcJagWuEKdhjADWyTbEEi5wzSOeAABM4eiFwCEDroAQQuBohcEhA6aAEELg6IXCIQOqgBBC4WiFwyEDooAQQuHoh8BCB0cAcIfBgg8pGA0EEKEPhwQOQjAqEDHxD4sEDkI2PvuJD6nEDeUwCRzwJS+lxA4FMBkc8GhD42EPiUQOSzgtplHCDv6YHIAaQuEcgbWEDk4AykzhfIGwSAyEEYSL0/kDdIACIHaUDq7YC8QSYQOcjHFQ3E/gyIGzwEIgfPgdjzgLhBYSByUB6fqGaVO6QNGgCRgzaEhDaK4CFs0BGIHPQlJkBukoesAVMgcsAXiBOAJJbeAwAAAPAMiBwAAIQDkQMAgHAgcgAAEA5EDgAAwoHIAQBAOBA5AAAIByIHAADhQOQAACAciBwAAIQDkQMAgHAgcgAAEA5EDgAAwoHIAQBAOBA5AAAIByIHAADhQOQAACAciBwAAIQDkQMAgHAgcgAAEA5EDgAAwoHIAQBAOP8FMWct4oOtDKoAAAAASUVORK5CYII=\" 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\" id=\"image052511c7d8\" transform=\"scale(1 -1) translate(0 -266.4)\" x=\"55.345313\" y=\"-10.711219\" width=\"266.4\" height=\"266.4\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
        "     <g id=\"line2d_1\">\n",
        "      <defs>\n",
-       "       <path id=\"m8f868d4a89\" d=\"M 0 0 \n",
+       "       <path id=\"m9925abfe5b\" d=\"M 0 0 \n",
        "L 0 3.5 \n",
        "\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8f868d4a89\" x=\"55.345313\" y=\"277.111219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m9925abfe5b\" x=\"55.345313\" y=\"277.111219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -247,7 +250,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8f868d4a89\" x=\"88.609312\" y=\"277.111219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m9925abfe5b\" x=\"88.609312\" y=\"277.111219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -299,7 +302,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8f868d4a89\" x=\"121.873312\" y=\"277.111219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m9925abfe5b\" x=\"121.873312\" y=\"277.111219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -314,7 +317,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8f868d4a89\" x=\"155.137313\" y=\"277.111219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m9925abfe5b\" x=\"155.137313\" y=\"277.111219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -355,7 +358,7 @@
        "    <g id=\"xtick_5\">\n",
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@@ -382,7 +385,7 @@
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        " <defs>\n",
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@@ -945,7 +948,7 @@
    "outputs": [],
    "source": [
     "# lensing_map has the option to return either Sigma map or the convergence map.\n",
-    "lensing_map = mod.profiles(Mass, c, z_l, z_s, sig=True) \n",
+    "lensing_map = mod.profiles(cosmo, Mass, c, z_l, z_s, compute_sigma=True) \n",
     "\n",
     "# make map\n",
     "Sigma_map = lensing_map.kappa_NFW_2D(npix,r_max)"
@@ -968,7 +971,7 @@
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        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2025-02-04T16:11:02.115053</dc:date>\n",
+       "    <dc:date>2025-02-06T12:27:04.570164</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -999,20 +1002,20 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#pa3622a34f0)\">\n",
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\" 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\" 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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
        "     <g id=\"line2d_1\">\n",
        "      <defs>\n",
-       "       <path id=\"mc502a15639\" d=\"M 0 0 \n",
+       "       <path id=\"mf2a17094b6\" d=\"M 0 0 \n",
        "L 0 3.5 \n",
        "\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc502a15639\" x=\"55.345313\" y=\"283.910437\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mf2a17094b6\" x=\"55.345313\" y=\"283.910437\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -1072,7 +1075,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc502a15639\" x=\"88.609312\" y=\"283.910437\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mf2a17094b6\" x=\"88.609312\" y=\"283.910437\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -1124,7 +1127,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc502a15639\" x=\"121.873312\" y=\"283.910437\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mf2a17094b6\" x=\"121.873312\" y=\"283.910437\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -1139,7 +1142,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc502a15639\" x=\"155.137313\" y=\"283.910437\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mf2a17094b6\" x=\"155.137313\" y=\"283.910437\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -1180,7 +1183,7 @@
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      "text": [
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:138: RuntimeWarning: divide by zero encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:202: RuntimeWarning: divide by zero encountered in divide\n",
       "  oper_1  = - 1./(k[:, None]**2 + k[None, :]**2) * (k[:, None]**2 - k[None, :]**2)\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:138: RuntimeWarning: invalid value encountered in multiply\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:202: RuntimeWarning: invalid value encountered in multiply\n",
       "  oper_1  = - 1./(k[:, None]**2 + k[None, :]**2) * (k[:, None]**2 - k[None, :]**2)\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:139: RuntimeWarning: divide by zero encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:203: RuntimeWarning: divide by zero encountered in divide\n",
       "  oper_2  = - 2./(k[:, None]**2 + k[None, :]**2) * k[:, None]*k[None, :]\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:139: RuntimeWarning: invalid value encountered in multiply\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:203: RuntimeWarning: invalid value encountered in multiply\n",
       "  oper_2  = - 2./(k[:, None]**2 + k[None, :]**2) * k[:, None]*k[None, :]\n"
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\" 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+       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KAN6sTxL0DUENoqhh0vp3Vue7wrxkXs02O2Fnai7E+7UjNKMA5kdEzbYtVeOxeXtAnG1H2kqJRkMuOfWiHbxp/dqf0Lp3NbdBtemq1DlTliSdrN1liqb7CJbWLCLNjXrVyXLqIV76dqAcmDuzpWW22KQ7Xm2pWN9LybGWyt8C4oFI8yFSbkk6Wy8abPYIo+PWSgOwZ5+BGgI9nLc/zLMv2aQWi+QALu30LN3GEkhmjs/m06XbEQN3DtjFD/lKjXevyd8qJLZKYL+qslS8EI1QYY6jlhAPRgeANxsgIqhz3zcEoRPQQ/XFzr6ZMC/dCaN1xsrscXxLDmjp/IooUePxkSiF7+NM5Mt5EcYyO7sVGZGzzbrvP5F5flvQ6PiJ5WXqpOUU3/lJ02QCvCgKGVv/hqCCSpsDvVSdh3y0QPpdYB6YV6XK7ykyIN7qRRCxckpgvmtkXXFVqPEcEO4N8YgfXq3CewO8gesBtHjWio2CxmRdekhXeqiuXHUeqK8LzFPl1UYK/AdyqcTi2PsNQRJL51Sx55XdZl4niIeO/14qXMiyqgEeDbeN3pwRWhTeU6Wnyq5R56HyUmXUwlxosWSr8pJgyqq+u5MsfHQbeyspBPFkdSr+l84vgHnMkhGmkwS77kuKbKXGo/tqR4hz0UOFZwI8K1rzlfzxirwV2CtUuqjswvmngXkqPzNPfLkLxE8W/vwDItefTqWXgzqdNleZH67KMyxCPv/6tdhSIXFaiMeiB8BbczRQjsxaaQH2zPyiFVZxdg33hst98+qdtfRJh1wczBE/ssd6l9wsBDm8w+XGPfh45ryVfrpb9Wv2scgVZleIB47PuHUaKEs6H4X9ei1YKSxj/xdL0PyC2APofJ5+ME/Ww+VrocpjeXZW7DlqPKSO97iz06/7MFXecztK9q0W+3BgWhbEmTgdwEuikqmXwmrdBtDIObho3lSHUqA6trxQWYafZ3eEzX5i1HYvYepQxsvL1UOmbdOTegJtFEUqL9suZhk7RbBp1EMXQjxaT2J5TGysscLGl1bKOHmcNJuNOU/GjhdJJbZK7aV+oG73ijNdr0gIMfWweSXlpObZstNJxGU1zRcIbS9Jmh3LpWcWYR6xQi+oJ2i1COoQ75DB9AIl1FuVi+ZlnmUqdqwciOfcwZlKW9rJGq4wM2/pqKY91LgU4oL2dYG4RIVHotmgi1ieRqyl7NahGU3gXtLwVkAv3KA1vnlyx5RcUnJpJTAP1ZkzfycJ6UAxosa3+fiyaiBbPuSQ/qDLsNNKrNmOzPxsiG/yJ+oogXjED2ejUMABHQHeCN4pNic98mZgPyPQA/OiHaFcGV7e2Pxo+prOz6pt08hsbupZG+/3dn5LaEpg3hTSrdZVq4dkpeZHriC7QdyL8HEZKCM1DzsAvDByuZvd2VkN9dwzVEugZ847Bcy5KFHllcPTaseSs0sVUOMSiAfrUUb0F8srrTukypdJwVbKImudV2zzLJvOK3dPiPNtCUxPzOsC8Er1XcPWqs7OTT9g7p5L86fyCtNGO0WNl0gwj+3LshPoCjBu3k0HqjefS7+mDXR+hr5zZXLzA3VH0+zYGcqFFOL5b+2Z0nMdn9HOzSPCtkUEWeG8kLJNfi+DuGhkSs6olAqAJ6P2BCqMlodV2+eR16j1xiq9ym7xywpe0kWsEJI3OD+6Mwo8y6UOoaIqfaxow0hZGEHFG8zbyyMPK/NYG0PtbBqZqjmWP3lFJ71a7ADxqJUSakMNxBsziG1DDSMj7bg4Eza1lpfviNWccmKqOTNtVJ3bGS3Uua/Mvbyu2vbKJb835afUsJNXwWwukbbLECyjofLucePLFqzxtobaEFLWnEL3lXmLaKruK5V6UgBEIC4VKE2tlF4qPAfeBdEU2oHo/jxyoPAslFOv4Ewc3Jgt1Hmub56rXvw8CYUuUuWdRWMyEio47pnzjc99+TI/P1xXrE3TxINXqq2+5gYdwSL0hHhLFV41EKIkna3XFDIvVK+g/vLnkVecnYqhXpmuCOihnYSDecJqKToASi2WSDpxeGDIVpKCjcxbE/R7GuKld3nK7+bkYR6btk2Ut/KMt+6bbEenOWWWSjOIM8dLVofmiQFeHBV8rXuMbSXYs6EurasW6MLySnzzpjBn8wkOfD9NLjQy4SLinAj6PmDTEJW+DahkqKEoTWK+2WyLRI7QtspQ46ylsjfEvQiq8BxxhQYAz+RZk37BCmFs47IU0MIKpI3JLC/bU5e0O5FGIbD+QvnMdtpmdIr9kRjRku2ZcyNZaF6mbbF2twxjVB74ImnDnYpbiAfLj9VNwve/ff+aeuTu98jVybzRevjrRcGB2p8XmrYDxLNtlEAkAZ6KTOVdHJXADpUXfvlyiwoKyytS6YVpuqnz3so80kaRKg+VsyN8pA+g6nVzUP64cdkJqHtU2C0l9x2cGeLF/V85aWxdJcp7J66GrRU/Q20jCsrJumzpBfRQHinM/cvYIKTD5Sd3eInqCh1UqQOn5GSQGRaQ0meJc3ljZUvSxOqItaN4qGHRSTY1PyAepPtFap8WCw6/XKEfniOcsA/Auw/UkJaTKC/vhiC/oFIVQssRliG2XiRlm/B85SWJ5mGm5VotUpuFLYudP01jhyPWxI43BoVUcHLUSMb0ra1inOnUPglZLN2j9dDH2MnbBy8qIO6kqwA4E1UWSobyzo5WarswDu3s3JQhjGYqPaHQg3kE03KsluiBwKZJdFYteQIdYn45/vwIQFrf4Sj1tVMjWXLtlVCe3BNHj4iuY+k28+ZHLZXQvhVsw/r1FBCvOM6d8vdW3i34OYduun/WNiwzr/iyp3BDZ9ktzLQmMA+mER6YNSEBSm4EbJSYVVE0pjzwx6YVwtyf77d5SVtst6RHnFRHbB+R+OKtIC48hoAC21M6HwXWSSu+Ndqetu2a/qgaSsPFAVAXlRmbz5WNyI6UmLYLzLm0vhILHcCp+aFpmVH6LJTQNFZNI7KtEmn88iS37aeiiYqPbY/lU6jGuW3MlLELxP3IAXioDDpPCHBR7MixVIQ4HfTIuYWssuz88nLKonkT+UReuk3DzY/MY/1zLr03beObG3+Gm5b1zINpZu+apvXbbf1ymyaSdl0GxhNnpwnKqghOqXMALyp7/nR2L8YP7/7QrIQ6jk4LleVDPJq2EcQbAjwYBUIs2J7SenrkYyKnvVmdndxxXRwZcGbzSUYW+ADNKSsB9M065oDmTXMAbBsWgPnSbgnM/fpygE3bIVgGYIJai+F2YYvCnc7lWX4z5ab8wtEHDsIwX6fZ5TbLuHkK+VadoOwJI6rKhXVuVPw2SQriUTD3hviZAd5QbZfGsY+xXTLSQtvn6QH0LHVeAHMnbQrmMaU8f2apciHQQ9EK9DZ8wINpSk5nD01roe5vTx/YraL+GeOC9L4aj0E8NUKlB8TPBvCD4N2yf1K3HOLUxGc33l9uHmH7sssJTGd9PD+t93vTBslY88CBts5n/HImfTBYvz1xeU++58Au3oHIq3Qnrfc7BHHJyyT8vNxSpK4c3LRsNWyYwLpMr/dIuk2+2LwCiG/2bdeWiafdtifog6eOw8ByiflTw5hCtnXphwQAo2ZFzu0QDWpqotgzlHdOepFKz1TomzXmlxFS3LQhMd+c5mfnexbJpr5CVR5LVxlS8C3wJNM4gEuHM1KI2nKoOjeQ2yVdPfQQZEPpFvj6fpj/WQjx5XsnFV6owEW4yt1Gldu0KaxtBPbHsLXSAe7VYC+FeinQY/UxZYvsFu93jm8eg/kmvw/r+XMDcy5vaBrJ49gnjUEf9MxJGgrx0tvzbVhYa2WCMO/W8UnKcsqNQDM8bfpIWiqxoatOObL2BNNxv5EJ8MS6bg7wim3bHNwZgMy8s9OXoe3A3hXqgrTJtoROCjlAD6jzzcmkAObFnZ/SadKoyCsFcgzi0jJCL5CgMI9FlXdec9hweWPTIhCP2XYSiOeq8FYAf7PwrrC5K+/sVO5fRVT5R4b8SdMK2pKVX6I8/Lz+jh5SPYZJEzv4EtsiPq6Yrzecpmy7p27DD6nxEMRL7+zkytJenXFPvO7KAEB4fYrWv/sZHW5IoivEmWNEDPHI8ZnlfacihxlMG5r43A35eWGVXE3D/Chc2mIbRqrUM1S6WKGXqHMvz8Y3L1XmUoslFE7ZfDt6Rw7EaehE+0Z6YlT8c1SsMvctlikd9htXHgI7E1JLpSnEW6nwGgUu3RYF26yZ4m44qMQPZWZrhWtsN7g3APveUO8CdD+NB+qlPtoJ2hjmTr0ScHsQ94cZbp5L7nvuGxuEfpcr25BCTgHcT2eBTh+YlbJMip5RDmx2Hr+OTd4CNc5Oq4V4jgon0R3gZ4d3J3CH2ia+s/NMYC9qWy7UExcXrB/t5wsAvUqdkzRVMAdR5SGVHYI7+ztQRmX4apyDOAfw0MnAHa0yfVKgU5j7qjyv4Sa9Y27AqMK/Qw1YIBwBfA7Ee6jwDIA3Ud+ZG+sewe2HuLOzm2pvDPZmUC9V6QKg56rzmNVSBHMnDbFYJKqc/a02263kpqCQQpdCXOJR86NV0jCn82xbcxT4VJ8gXVT18mBnH0+7B8T3AvgZ4d0B3DVtOsednbFCMpeuK9RbAD1HnbeEOVdPoD42beB3FrAZ4EefPJgozkKcA3joJiE6IoVaKhTmXNBt5dsvtXd/Rm0V7jc3PQLjU0C8B8D3hPfJwO1HFcj96KLaK8CefaJJQT0yPwr0UnVOvm9881yYr1/iFovTKK8e2hB/fmyZKyKkxjmIS27TZ2/PX9T3BPOYKq8OAx76nK0SU+MLiCOWCsoh3luFBzdVQ3ifCdwtoc3FhV0xDZehOdwrRsZkqfWICo/NZ4EeUudkGgv0mDpnOkFZmDttZmAOmzdgsYR++8szTzeQvYiZRmoseArim9vsE/XTkSnABPQUzGnZTdR4CHgZ6tyxVHwoh9oUgnimCj8rwIuAeWfQ5tYFr8h3hntT1V4A9WgbpCq9BughuyWiztlOUA7mm+kezP02bKCdUOXAZK8w03Ni86KJQLoYxKUnEGqp2DI4mG/ywdsdFOqGIRoV9s1DahxeI7jvIUslB+I1KrwVwAXrtniXawjvruAWli23VjrCPbQiitZ1oWIXqfUY1APz2HJ9oBeoc9Zq8efZwmIwJ2kUIhbLlIBZ5jTAzVxGrlJPjRv3bRcuHxfUUgHgjlBR8XHlOWGMkh2HPriX6XB3RqK8Fc3jKHIG4j7AEUlP53nfcwF+Gng3gvYRSlsadR65X3HbK5R2yj1TsTeDekqlC4Aeg7ktM6S0FybHYL4pT3Cj0Er+aLqpWLlSZ9/6Q6ZpFYe49FG2m4dkeV64UgYaajOShbYJgNxSsco71TwL7hDUbf2B0Suxzs2mEG8N8JPC+8zg9qNpZ+felgxQsL0yFXsW1DNVugToziRPQS9pIko7CXML5MRJJajK53kGBnbEdYlPToOrgg4z9CHuKHdhHQYhj3xV3loBIzyIo+74MxbUC9wDLebm+ZA127ScncLbJWHoNwV4hfoW70JfGLS52HZ2NlbVwQXoaMtUwV0IdbaeTJUuAjpntzDq3IUzNlZLEOZMeUGLxVkegrTW+wwmyEaHJiYgnhp+SIGcslXsb43t24WahIVyFOpzOzb++fpVBHGhHx61UWoAHgFaFkwrtsMZPO3W9WwVeW+wh+ppWFcV3P2EArCzZadUegroKbvFV+fKK4frBGXSO8MSyfwF5k7b+8KbC6UMq8bpdwnA/fn2jk1gVeerEo+r8q4RgXrMF4964h7EeZuF1OO3h/vulxNIk5weKmeTv2z9vwloC+pKWysdgSuqq1GdxXAXgD2q1EMqPQV0Tp3Pv1l1TudTdV4Kc0zgMCFwOwVN3zf2SsiKKQhfjfsQ5wAfinG2UOx3uxRaGYxAUJVXhQFvq1Bwh8BosPXFQxCfIwnxlAr328KVHUsfmhbKv8mbv967QHtPWFfUWeaR7wn3WJ2V9RZ1pgpsmKBS56BeAnShOi+COdcmp/xFsouixdBEG77d4kM8NZ6cGz/OPU+lqY1iAkMMg+mx7jgU2OxvBuImA+KZKnyzCXMUOZd/kzdvfTcF9xHAblhvu87ODqDdu95s1Z5Q69GO0hAsybQg0CXqPBPmTkWOgxIYxbJMonnCwDZz+cknG2IFtrVVuOGFIYjnvOrNQpzC3B9muIxgmRfYAj7JpFQaTo0HFaw3n8Ie7vRciPcGeHRzZ4C7GbTvHNihuER93hYRW4CekG8E+Cy4R9R6EOqMIt9aHCRfBOiOOveKNRT5DMxXse0p7llROxYLB+z5hLAo8JBqj8A+FnoBu3Gm0c/QnZ5+cKNUNh45UK7KEyNRRA/bmsHNdm5SOIcgnqPCSwHeCd5NoH0EsA+o066riz/Bxi59O0eo+AZ1RpU2N0MCdUaRc0APdojmqHMpzGlb/Pb4ZxXm6DNmPQW4zy13fy+LLTyCrXIGtnZLzCv3OzMX8MO1WSStCPnnPqTt+PGg1+4rc2D97aRz09RAPFuFCwB+GLy/EGDbCK0n8fPIgZ3gDshWVOu2FAJetJ4iFgx7ReSrdIaXYnUegznNGoM5IhaL32ba6emfsTxrI+cdnaEnHPoqPKbGuXnrDUBb9a2cM2c6NrBmfm86OSPhWCopiC+/hRDvCfDEOiuC9l7wPBDSfuSspyyP/FC4byoWpGnRNq6eDLiz64dR61GVngt0qs699jugniV5EOa0TgQsFr9y74REbw6iFxGS8P1x643rhMWiEzvHiLClArjqfLVZFG4ZB5bDQ25Eig/0kKXiAV8McYkKLwR4d3j3gumJIO1HrZ1U3dkZasBhgKfRC/YZcE9aVnZCTKXnAp20iVPnazEJmG9UNQNzP+ZCDMxqnxCCUyVe8vIJZ/EI0LUyDsBjbwjSpP0U1q2eKe6UY7w0HNRpWgpxZ55KQlyswncAuBhMreB6YkjTaNZp60XbW/RJpBp8CtAD6R1A2k4h3INgl6h0mjdgUS/pQurct1okMI+CO6LKiZ3iQNuZzlssoZEqVo2HIB579sronERmoHsw1yStVgY3bwQL74tTcCsyHez0oBrfFLzOL4F4TIUHAV4IbxGgaiD2hYM6FZcNHHaKnAU+FPqxdqbaxSjkTRE+rJ0va4KoSveAHlXn3vbOhjkiFovTtrXMxV4JgT0RMS/dh7jEI3dGrRCYB+sW7oAcuB1bJTICJWip5EI8R4XnALwE3rlQOymsj4JzMki7LqEZS5xAOdeuyG4nglC7QvUlwC6BelClM8I5pM6N15YV1li+ZcMc20zOzUBz/QaR1cOocx/MVI2HIC59CqK1UyzM7TS/49NX5ratoTD+F0OGHFI1TtPlQlzih4dUeADg1fCWHqc7g/G0IM6JxDLk36J/ArDnRs2GLDoJSAEfWbdRqHMqPQZ0v5rFr4YLa6KuxTDnGkEzU4jPKpy+eYd+xsLaKuw8AnZE0nER8salzx+3ebefNoH9pMrc/hHbpgHEewE8uDpbK/JIvAkYS6NgWfM98lwVeuch3YFEwE+dFA0/b6vCeZUeHMFi53t1+1aLr8mTMN/U53k7DLydNMpELZaQd07VeAjioZEr/oiVaRqgyaXCuKxMry2BjbxCWzmfLNS9NNQOkUI8aaX4AAfcOsDNbwDvAgB9UYDmotHy979F38YbBb2Nos5dLk9QRm/rcaAeAjrJz/nnjjonVUVhTtq49cvhfbd+ClHm2O4OMaDHnqXiQ9wCXKuRL8zopX0+zOlGorD3bRXaZv/7MslR4owaJ9/9USpJiJeocAHA+Y5NZlpsuhcPUO9TTbdRK5u4lw3a6YTD7dAiuHNg96Duq3R7byIHdPY8QdU5o74dmDMFLzAn1sxGlZu5JGMWhU6/57yIwh9qSKdRgHOjVpb5Ri8wX9LP7c25LZ/aMlSB205O1hsnapy96acE4jkAT6nvHKDHyukZ98KTneKwUSunjZY7SGJ9hnZ85zjjto83LaTSc4Huv0yYhbk3fU2rYAyBuT0rLJ9YVbkzesWFeGj1c89V0cq1WSykU175AvQZ5st0TG2zKjykxjfco2k2o1QIvAUQpyBmIW6BTRti8gFeA+9iYD/g2zbI+oyPWnmAvS4kOy6zjv0DxXDUtXkDUM8Bug9zYAW6A3PLZM3DfGurzJ9ElVO2Kw/ok70SXmnrs1HWNBTiG588SZwV5svdnTAYoZLDDqf2ugA3cBW4q8a9dbL5W2GtRprWhXhQhZcAXAJzP08oHpDuH5F1HLdWHmDvH6GNQ9a1COy+9+1UEQA6sVE2xRF1rkgZgAEVsxTmy4so7EnEwpCo8gXWM/hg4h2efjh+OEMYxzMPXYZga5/YPFaJS+0VY0CsFGutWCXuq/CQGmcg7o9MsdtJoMJ9gOfCOwruB7D3i4x1neeRC6Bzujj7jhdad1y7PW98Scooc6qO11ErHtCZ4lmYW9Aqos45mJvZYhnNPBhbTcNBbP2GgInx26UvYKAPyqJq3B9bvgE9vWJYwlXl0huAls5NAvClDrOut+VvVEt1yqh53CNWiI9CKyWiwsUA989vofWec+zc63F2hmiw7tp0duY2RLJSz75jtIrUcob8cjJv65HHi4oBfbE/aB5WnTMwnwHu+uWkUbQDcJ6vAMdWMUZhxKzuzdQgBf7GoOlzC3E6zw29rkcP5qMZWCW+rLPZShmJpeJ0dMJT5r43PicKKvEAxFkVLgV4LrzfshJv1f6Tsmu/USs07n2nQEWHjxdJ8RdR5hzYg1An30VA939LYb4Zh0etFeOqcs9eMbGzELajVajyphC3AB82G2lcclKYj0Yt3rgtVysDE7FY7MnHhTc8Ne7B3Pnj7RQW4r4KLwS4qIMzNj0Sux0PR8dJ2XURXkm++ThqvGtOvcFOT2BLXsTFvDPfqMnS9oC+UecSmM92ihoVjJ5pRC0WTpU79sr2ued+2zdjxz2IW4CHPfL5Rvx5+SYlvpZ185S235ZQJ+dWjWO1VAygRrVMy4G4r8IpwFn7JATvTBV+xDGRW+eDXdM6u9gvNt7qijkK1ADkZ/HEug8tAytkvWkSqDsKnZzgl6IMnFEtSidgbohfvkB8q8oxWyrGVoK0OgdWW2X6vkKc2itOeswKWwEW5vamH60meyUW/pjxZeRKTI3PVS2WSgziY1yFswqcAXXTzs1YNNqvayLV9i+FZxtrJThC4g5iN1j3qienXLJdkp2foaze1diqwFegOwD31flop0/q24G5BZOe/XLroStsVLkhgF+U7aySQ2h1vHBsIR68s9OxVUZoo5bb9nWkt3WcZ7mWilXonhof1dyZqWYAq6Vz04f4otJDKtwBOgPwFLxzwd1j384tsyFzYsv6ltiW9MjPBva7h3WrkIBakJxzayjQp+9mBbhNaxW5BcnowdxaKyOmzk/7MJPprhusj7adIKgWQE6fk289ffow998OpJXZQNy3V8ZlSV1bZZzz0bcE3WzKeRr93CpxosZH5YxGWUDtQTsI8ZGsfwfoAoAH4J3dqXmGiLXvC4F8LueyOzujl/cN4hAL5Ow7dm74y6M8+4zJkgQ6sVsWdW4V+ZwvCHMLIHsWmBU4rJ3iqPIp0TR5vbSwQPdfHOHf0ekqc3K7PoBxuZOT2iqTKqcnB3uCcVap7Zi13433uUCZXLZQIFOIj9xolbCNIgJ4DN5vaf+O7bwNYy/LphXvmo1aOdSDzokTtfOokS/Km7fwUq3wprbLNG3tEHUUOSnTPn98SWdhvpwKzPQiznGqZLGrZ8U/qXLjPYxqGvLnj0DxrZOtvTIyPjm9LX8C+I2sjeW2fZqDDDcEVktlHXGDyUrxLZVxVeMsxD0/3E5b1jcD8BC8a8F99yNOdoK7U/yJOAIcNfxwzzhwhe+1sbPVQwDshs5XK2h8oENNP1aPfFbqelbperIZojA3ZuKq9cxnhlLrwu/w5O7GXGwVYq9c9A0Dth75oICbMriOw2KrDDCLvULDr8tvl1XhZlRLf8CiyKUQd24CEgKcU96J7X/a/bBnMFelbzneHsgPAnf3nv/SUHzbnIOKKjtilfgqnY5iWeS0MmS0CpxO0AXdek4/Gig1d36Oc/4RazmOZTEp8dEQVQ446tjGosAJxLlb+EczN04D13FYbJXNuvE88dH4/vicZgE3UeQGpHPTg7jf4WmhHgN4ylLxIrgf7rCfJZOk9sOe8cbBvj798F4X7F7AXdDOFkoqVMRGpHuyPGyxzL+Vna2gRuN45+sbjOf5S4/oNEZ86fwcp5ZM5alZ5WuMaoRSClqvEA+FtVAG648TiG9UubJ3do4YlcIANalxxlKxsQAcwDgqjKOCGfUE81mRw+/QpEr8Nq1cRdT3OuyQgTgD8Bi8pbZKk30pxgjpjubP9vI9wJ4Z83Jc/AmnX6B7sUoy0ja59CVqWlS2cQ8aR40HoG6dDsdOWSCMVZ2Pq9UyWSYz7O3zV6xWt8b6CJi5DKONo8oNAamvxv27POmt+hbow+yl3wzxfWx6Y9iyMNdl63T/Zt4uEMeizJcRKs7oFALxDcwDAKfrPQZvE5gujcA+E4qigQ6ZwHQ65R9WTDi89m6tlTMt0IHQtiE+OITpWpdXk0f5B/IM96WNFOwGG5XOAh2rOjeYuTmrUtuLuTxkS5FKbFmjgsGkysdR4aYUtCFDAL0d0ipxqsaf1A3DbLXY0OqGUSloY/CKAYMZccUwd5BqXEmZI6ytM9kqN6NcNb6ocPqHBeJqnJT4os6nQh1rxRl66MPc25bRadjOy4rcfEKxEIRwBl8OgzrAr5cTszDv5cu9F+QE4AbawlZUVk+4S8oMKHMH7NQ7J+k2QDdqslbsghtMw7bn8eS2hGkcOWAWI34+WEe1jk701LA/rtsPq8QtxCnMx0nuA2qcAK1UcJTKsmpo3dZOIZ2cFOJq/r6BOLFSqEJnAR6Bt7MftYJ4KrjVLASc2DIR8uVQqC8Ve79PxMP9H2N7Elhz0QrgTeDd6iQhCc9moXDfqHDfZmGAPmUk6hwIwxyYnq1iOz3HyUc3SmO0naOaKuTtzmZHrdDnrlhVvqTBZJ+8zk85tFbM9sFacOoysxqfPHENY60Tq8Ctur5FIL58p5YLWX8+wH14RyDeckRKanTTVCGXMTEf5LwusWGE9sthQLcRW/c7M/GYx9ieKHZT3xXgTraxwfr37RTQg8WKZppGrd+Nzb+o8ln8WnVujWUrfg0DczpLqWlQy6iglMbNjNCjws0BuqukB0zWypO6rdaKGjHMJd+8I2saBTN60/RS/s0o3EY12yqaWCsK5jaBG6OCunkQv5EhhoudojxVzgCb+U63QzMrhQt60maCG+Hk55XOFynre1LpodiZiW9v+KEwTgHwEni3uBqIhafOqSIHiBJXZLq1Vvz09mFZ2kp6EN+cwFxhUt4KU8fnbbZARg01fxo9euPLV7+cPs52UJO18qRuDsg1FEZis/hvEbJlbeycBeJ6hrhehhsuyvs2Q5tC/EZUONPZuaxbA1d5C6yU5iNQEso7CswUdCMq+02q9IPiiwP5bvZJAYhz4V11BRAJ5R+c5CChqnwZlmih7gOdwtyqc0tzTQunNwxNmc1tslSMmpTwbdS4jQbXUeNpUJtOT/8BWnqG+TIfwCsmoOtZzW/GmWMq9zrquT69qnCqxG9Wic/wHsmntVJG8pvaKWTdpEapRH3x0oio7yDcW0BdAHS2TEF+rqwvDehfDMjPCvAceGer9BYHPzmAHGvFzB+ezYLZK1+mU4VuJrvFWKsFcwH24LOFXqdxi0YrjErjdjPQ2uA2Tpo65JdTNf6k1huDMOex7RyVdvxzeGUaYLJVRo3bTU9qnEAcI1aIX9Wqvq0yXzpAt1ZKaIRKENotL9Gph+VPx3b/8oeh0rR++iDUM4BOy3wAPS++CJDvAvEWAK9NW6LcI/n8oYnLVwJuZ5SLVeTKVelGY74xxv5ZeJvVNyeVmYsBbgpGT8MQtaaqfFbKxMu2sTxvBWbxy5dx5PMTD0fo5S5QGzcC8RujxsfbbKnMEJ/gTSBuob1R5fOSsbfie5YK+cw+YSdgxQKZ5kuAOkeptwR60nIRQDpZzhuJNw3yewa4KF1pvljaRD7HXgGWg2kRvL4iV1ifhmgwjfrQmB+BO93haYapKmqXGAXgChilcNMaSk+q/PWmcdEU5trxvIcZ5pMqv5LH2a5AH+bx7FqZecy4XiB+HTVeb3pR47fbrMavc+cmgbi+zSp8HqmibliVuIV1RJE728Bb11k+eEJ9sta1r84jUA8qbwbGLYH+UOfyeJMgLzkIisqqtUUaAVySJwfwsdiUo7afG6hbn1yBjFyZ/4aVKJOhopxycNUw2uCmNbQ2uOoB12HE1WhczYDRTLfyTE9IXG8MelJXPM8dngAwzBVPww8nC4aOS7+aYSpz1LjeBg/iOg7x26rMLbyd7xy8EyAviRxgb+Acg7pUpUuBzjY0MB1t1TnbpjcQbw7k96rCmwA8c364vXKqmPmB5Gr55ylyYFKpegXGch+Ob7UYM49WVMvAQAPAXDWmodoGt2FSzK+3AddhUuM378icLBXjWSsGN2g8qRs+macl7c2sHZyvt2FV41eN8aphrpOlol5ngL+qLcCpveIDfIQDa6dDk6zmknWeDO/qKQX1jQVTAnSvaSyED1TnwTbdebwZkL8pFZ4D6Bx4b9J6E3JORKGZizJfOxedJyJqrM9j0ZhsldH+KYzGAIMdLmibpWEUcNMG16vGoAe8jrfFCrmOw6KuB5i5w/M6WytTKRoaNyi8qmEZkjgahes4LKNUXmc1fr3OavyqgVc9QfxVQV8V1HUCt74SiBuEFflGjVsiydexD531IWReuuig6zTUS4H+UOfHx5sA+b1CPFeFxyAdHaoWUn65Cp4JdhkUpgGFTifoDHZGkSu9vAEOeh7VMlnpyj4gEUZNnZ83a63cBryMA17Gy6TKoacHY2Hywxeg2xe3KWAwZvXKjcYNk6J/GS94GYcJ4jeN23XA+KqBWYVTiOsrnE5OTX1xZrihIiN0Sm0UZ7QQCb8YRaYY+7Abm08C7ZhCjyjvanV+EMxFZd1J3DXIWwI8WV5viBeqcOmwNU4Jik8MXPv86dzlMO0IVfPt+vOTDqk6n81xQAPjrMzViEmdW5tFrar8VQ/4PIx4vgx4uQ34fLtgvPj2yhVPuOHZjiU3wE1dATwvaUaj8Pl2wcttLuc64PV1wM0q8eukxvWrgr5islWsIp8B7oOcwjs4OkW4/jbTPeiEnIkJ1GZe9wo+xGmdDoS9tjiQK1XndwJz4L6Bfrcg/1IgXqTCOQWeyCc/IWAbW2nI/l4frmVghyUapWAGQM8gh8H88uVJnYPCHHPHpxrwOhh8Gm54Hm54GQd8Hi94NdNrmgc1qfHneeSKjVcMyyiWVzPleRmnE8Gn1wteXy+4vQ4wLxrqVUO9KOjPLsT1DcunA3JjInaKYH1500IAdYZ7UphRKDtFE6DbmQEV3kqdnwrmCOfPLu/EcZcgz4J4bXlngXgpwMl0McC5ukrUOjDbLHMytf42CnMH6PTKOKPVoszNAKjLpM5hYT7bLEZNHZ+vg8HL5YJP1xs+3Z5wHQe8mmF5psoAM/vk692dw9zJeYPCq5lsmU+3J3y6XvByveD1dcD4MgAvGuqzgn5R0K8TxPXrCnGqyNVo4h2bwnXkrE7qZxP+suvWhzenskMKvUad3wvMM+NeYX53IM+GeCL9m4a4BOCCeVkK3m8DVjWoln8r1M2szKHml1IMgBkUxtsEc3unpLLP9Z5d7pse8FlfcNEjfnx6wg+3Z/xs1MvDtPR8Q9B75zb9SdePRuPzeMGPtyf8eH3Cp5cnfP58we3zAHzW0J80BqvGXzH9XVclrm5m27k5K3D+xLddF+7KIqvSAtVT3XQat6v5Aj4MeVOlzu8S5pG8ReWdMO4K5A+IB/IvcI2o8JjKTgE8+Htb36adgNMJB8AZZ768GchaLTfADGYC+s27c3I5ujRGDVwHg0+DwcfnJ3x8esaP4/Okyucx5c8Y8WThjWnazaxq/OP1GR9fJ5BfXy7A5wH68wTx4ZOCfoELcgtwp00A9cW55ffXhQMJon6NUiuwCUxSNvVShiIQ8pR2VJ0/YJ5f3snibkDeGuJFIS3zpBBvAfCg2hcqdYAcT2pK5KpztQ5LHMz2hhv7LHBojGrAizb44ekZH55e8f31GZ/GJ4xYH4r1PA8/fJ2njdD4OD7j++szfnh9xg+fn/Hy6QLz8QL9o8bw4wTx4QUE5Ma7ixOTpRJR4bEFt9YSnWYsYBeIqyTAN0D3p4cAv0DZdIf5JqRAzQSvKN4wzO8C5D0gXqTGc8uRRM2y9YK4FOBsOvvduPP8tttwrJb5pRLzaBajFfQAjBeD8QqMy9jtSble5yeK/6jf4bvLDV8/fcD3797h0zh54U8Y8W4u/8VMQP80PuH76zv87uUDvvv0Hj9+fIfx4wX6o8blR4Xh4wTx4fMM8EWNY/XDFyVu4hD3LJNpGqE5Ud5Wia+QNlGgRyEdmF4Cc1HUKGVhmlZ1vVWYnx7krTs2k2WG5vVS46G0ITUeK6cC4nGgmzDAne+Gnw6vrEBQZW5HtYzDBNLxqjBezarO57tBrxhwHQy+f3qH757f43fvP+Dj8zu8mmnXfiae9Ku54OP4Dt9dv8J3n9/j+x/f4frxAv3DgMtHhctHheHTBPHhxULcLJ2bajTrujKpZfF8keXTEHCrDcQ5oNsbfSjAHbhXwnxt9HaaSJVvFt4tR2KxSMqR5O8B3nuA+elBnh0dwB+Klmo8y1Jx5jNKOfK7FOKh9JwyZfPTe+6Zdq+Z529KwQwGgwLGYRqiOF4mu2N4Aa6v83NPbgqvuOCTBv7mcsPP3n2DX737Gp/M03Sbvh3Fogw+mSf89vo1/urTN/ibHz7g0+/fQf/+gqffa1w+Yvr7ZKY6Xs3ii+vbvAy3ULvhtBsA1LxCpo5cbJW4mtabnRcSxNP3VTWzahzkewHM2Q7QELQF00tiV1hWtvWMcWqQf0lqPLfsqfyyAlk7IAfingp3vGKqVC3AzVpWUMHbGM3yRiFrt2hlYAYFcwGGi8LthYwmeVVQRuMFF/wwvMdv3n+DX77/Ft+9f4+bUXhSkzd+MyO+u73Hbz5/i998/AY/fPce+u8ueP6dxtPvgctHg8uPkxKfIG7moYZme7Ja2jgvJrVNFJHLlroKgDYEkGq58piXFMtLNbAmo6COwXzZfhTSmeHAfFkwUn5u9FblkfgSVflpQV4E8begxkvqyFTjbBr7XQBx6oOzEA8A3AEi6Syk9U3f15c+WLgsnaAXjcsA3N5pDJ/V5GVfFdRV4zOe8ddPP8G/fvcJv/n6p/hsBuiZAp+Nwm+uP8W//uFn+Ou//QnUb5/x7m80nr8Dnn5vcPlkcPlsMHweJ+V9HZdOzaV9TpsM7KgbBczfDZRWxO+flTkButFY7BJXPNsprihOwhyMEvcLybVYmAiB7DBVXquqT3KCaBWnBfmbi0JVH5qfrcZD4J7nudON2w5PiU/T5BCffm8BPo38MPPb6FflG1rGZaiiVrg8aVyeNcZnjdcfp45K/arxI97j15ef48++/iP8+1/9GsCPAIC/GT/gz374I/z6r3+O8S/f46vfaLz/rcHz7w2efhihX0YMLyPU60i8cKZ+YL5D1YJaAfMdqtAKi11CLBUH3vbZ7AGYg1gcFObrtFU5s7YKkA1pG2zHJxcd1fQjyuIB8lbhcbWpLRQrK6XmufmMMufSbuC9TKuA+Ejm3YwHeLOCfhyXW9+nttEzzfQuz8tFY3zSuHy84OmHAcOnAeqm8RFf43/7yR/h19/+Ev/hu18DAH798kv8r3/zx3j9f7/Gh3+j8eE3Bu9/d8PlhxuGT1fo1xG4jnPb3LqAWXlrAHp65gu0mubpmd3UTlEzpvX8OebBXEFtbAiqwJdtFTbV3fBVuB8x4DaEcbG98ohknBLkvWyVrv54TtS2NZY+kk9SJqf0OaBvgoE4KPRnQG8gbtXvbVwAbufhZuE+Tr60Wf/s8a+1xuUy4Pn5gne/fcb73z3j+bsB/x9+iX/27T/CP/36/wEA/LPf/iP81f/1h/jZ/6nwzV9c8e63Lxh+eIF6uQLX2/w8ALvAav3TCtB6+j7MNBysR2JgoJcHgKkbYIbZ7TYKZlxhbgnmwHwQrFNs4cv62cw2S40qybUKROl7wDlUZqSuXm09q71ySpCfPXp0woqiYb2sxZKoJ9m56ZVBOweXk8ECc1KOD3HyidH+Hqff9nMcYSx8Z2A+XS64/OYdvvo3H/D+b7/BP8ef4n/4xb8NAPjn/8uf4o//J4Nv/uXvof/uI9SPn2GuV6fjUmk9QVtrYJg+zaABPZUPo2dQaxiMU/rbCDPo2eYw8yfxsccJ/NQGcdaRVJXTbRPoRGwKmYPU8llBefZ4gPzgCA07vOsIngjmGctQRONaJ6P/yUD8ep0AfrtN32/Td3O7TekBQCv89M8/4Cd//vfwX+I/BwD8w//299C//jcYP37ESNKpYQCGAWrQMJfL9F1r2ENj8akxv3R0VO6nUpNCNphU+whgiKjmt2InkOV4wPf4eID8EW83yGNlS4dqPuIR9xAPkB8cziNL30qsMtYJM6tXaAA3rCM/7GgNPUu75XMa/uGK2AvUOM62xzBNn60VdbnAfPUO408/4Lt/6xv8xX+k8F/8p/8dbkbjv1L/Gf74f/4JvvmX32P42x+Azy8Z1op2Ojedz3m5lt5OvS5rcN28hSDL8VDjx8cD5AXRDb4BAIrnZwRdhs3yBEGM+cYV43m6aqt47Sg2A0DPHX/GTp/fEAQzfQ6T16z07D1DwygzvfRYTzaG0drp7FxCa+AywDxfcP36GZ9//ozv/3jA7/49g//gn/wZ/uMPfw4A+O//yf+Nf4F/iD/4g2/x9V9+zXZ2LqUynZ1m6exUMIOdNrddgYwdV/PIFayjW2Dnc+tUkfy0nMCG86bTdE2BehCcHyeFsjglyItAKYBctNxQ/obwzCkzdx04z6wO5JOUuahmPx/C5QJTvctLlel9it5QPIzzqWCYnpkyD/6AWcbx6fkFE+P8xiAzJXLqmoE5Dz+8vb/g+vWAzz/V+OGPND7+/RG//Hf+Gv/05/8Hfq6nXfw/+cX/jn/17/4B/gp/iJdvL/jwG413f/ecNfwQ3vBDO3Z8ge9goaxImrmMBdRqWVdJWCoebKkRK1OaeLnJNLllemU3DeFJjUavtp71RHNKkN9leABtqtpj4I+p5xDY6bTQd/AAj6pymA3Mp98ezOcHXgEzxEdbyGSrTBzVU4ehs0wWggrmSeNmbwj6WuPlJwqffq7w4x+NuPy9j/jHv/gL/MnzX0HPXsefPP8V/vEv/gL/49//gB/wAeNF4/qVwvPv9TQG/fN0U9B0R6dhR+M4D8JSBNL2lXWaqGsK+BnaPsTFapwDuhJ896ZJVb54XmZEl+ERVfEA+V4hVfapdPN8TjlLyg1ZKu53OxZ6zbv41Mu0PJgv8LYZxskXN0atozwWuE9fDFZ4rs8pVzAXhduzxvW9wvW9wutPFF6+BT7/fIT+1Sf8yR/+Fn/69V/iF/qjbTV+oT/iT7/+S/yrP/wD/PltugN0fJpg/vR7hacfNYbPZrq78zo9a2UaG2+cNoG0aYHx8h0uwK2dkgFxur02dgytD+581mLJVtzkRBULabkPUO8WpwV5L3ulVVQrbtLWUFniOnxIB35z6puqbve71d0g3jYpah5uF4T5ME8c1aJuzUTmKa1WMOShWcstPqOZfG+4CtXYJyA+KdyeFG7PCtevgOsHhdefAC8/G2F+/oI//IPf4x9887f41eXv8E7dlpdMvFMjfnX5O/yDb/4W3728w29ep2ezmEFjvCjc3mF6HvmLmh6a9WpfapH30CwHogzAp/RhiLvT4E3zThqb+r19gnz6aXJhH1LzhquzMLJsi9qTREH+s9oqwIlBDjS2JyRlhk4EhWpa2okoCiZvtir325UEewTmc3rHZrHlUfVt74QZLUFsI9YCnSUgnrQZpiTTY2wVxgtwe1IYnzGp8Q/A9QPw+u2I8adXfPPtJ/zqw/f41bvv8O3wCYMyeJ0fwDUog2+HT/jVu+/wVx++wfffvsP31+mpiUZrjE8K4xNw+QTcLMydx9gq8hhbtd2OFNL0N1XgsN9perjqHdz8AMQZiJbCJvUu0ezw8hbbKicB7pkhDpwc5EWxoyqvjpAqT0135s8wz1TldDoFdQzmXtPW7/ZBS6QdK7BnMM/9lattsj0yNkpVK4wD5meRT6C9PU/q+fYeuH4wuH5tMP7kivc/+YxffP0Rv3z/PX5++QHv1ev0fs65ITej8F694ueXH/DL99/jd19/het1wCcDvOIyKX6tMD5NT1Qc7WveroC6KfJiCRW/o5Uui11J62rwQKwC0/3vYYiz9kqmGjeepeN80vTC6SWxKyhPDuWSOD3Iz6zK2XIqVLkI5rFyKmFui3BgDjijUMycaPPkPQDTXY5WmdvG0wVkAM4oU/qqN/tCifFptlXeAbdn4PbB4PqVwfjhhsuHK7756jO+ffcJ315+xAf9GU/qCgB4MeuSPakrPujP+PbyI7599wk/fPWM6+uA603hiunBJ7ZOMyjoi4F+VdMbiugLl52XLq/LtgkOetRCmdOEvk/pFDgAJ60SIcRD7d20O7Q8XPRW45H8X6IaB+4A5EABzAWqvAjmLdpWUdcm/QJkYrFUwHwLcFLk8hxsBui0TcuyKGxsE25ZQBT4rMLXly9Pr3qztsf4PEP8vcHtK4PxqxH6wxVfffiMb99/ws+eP+Kby2e8168Aphcufzbuy5ff61d8c/mMb58+4Yf3z/h8HfDDTWE0ClfotUN1APSLgr7Qly8r7+XLKg1zZnmXZfbXgfObB7jkdw7E2Q7OXHDtqcZrIZ7Z1nuAOHAnIAf6wDw7pGXmqvKQ+hZMz4W5nU3DUeOJ3/R51dPzRNxEi00TiY1tsEAcDsStLz6p8Rnk7w1u7yaIqw9XPL+/4ut3L/j66QXfXF7wQb9Azw9zGY3Cywzwca5UY8QH/YJvnz7hu6f3+PjuCa+vF3w2CiMuAOZx7M4JRcHYtwXdMMNcecp8PWuJl5+uZLtuybRqgMfSMvVt5+dN537v6Y23LvNeIA7cEciB9jA/lcWyB8zBTCPzkkAn6ZUhIKDl25/ccD1SmKvC5+8EnOMAmMtsq1wmiI/vZoi/G4F3N1yer3j//IoPT6/4cHnBs77iSd0wKIOb0XiBnm/wB16gcTN6eo+nuuFZX/Hh8oIPT8/49PyK203h9abmp9nqpd2GtEtdZ6/cAt0+y2WEo84NXXmxdeGtk2W9JKaJOjuj+bfbI5hHOJ37LYE4C8sQQGvU+BuGOHBnIAceMJfAHMDaAUqTRKDtLAtpz8Y6odM2GeikALzn30ZhvpEGix8OjaVz01ysrQKMT2ZW5BbiI4Z3N7x7N4H8q8srvhpe8U5foee3PI/QeDUDBhjcoPBqhmUoolYj3ukrvhqmvO+fX3EdNcZR4zaqWc9PpwCjAbxM6lwPmJX5BHRYi8Uqc6LQl/UNTGPlYxEDYERl554ApmkPiKfi3iAO3CHIgQKY15R3JpgDi6IGtkrbTeMBPZCPg7yzTLRdCEA8cUA6QLEQtwBXK8AXkF/I55OZFPk7A/NsgOcR+vmGp6cbni9XvL9c8X54XdW4HaUChVez7t6v5oLb3KgBqyp/P7zi/eWKl8uA69MAc1PzOyws0KeNoPVkr2gNqCvmxwgA+qZg5jcZqRHTwJ0Z5sYDurtCw+vLWWfcfCnAyfQagKfmnRrimXGPEAfuFORAJswTqjxZ3sEwB8rU+ZRGOeo8BXSbnzuB0PasC+Ol88pZ8lCAk5tkjMYW5D7EnyeIm6cR6nnE8HTD09MV75+ueDdc8axveDeD3MZkrayv4HkxA25G4zYvwJOa8jzrG94NV7x/GvB6G3C7KZhx+oN129UMc6Wmx5DPVxMY10/rmVO/fFHndh1x+1Bs/THTY5BMeu9+ebkqnGvn2SGeAeZ7hThwxyAHGMjFwgNSqLxDYU7bF0ufo87h2hyKFBqE91zf5uQiDQrw+ffmFnWNDcgXj/wyAdzC3DwZmMsIPI0YLiOenm54d7nheZj+3g1XaNL4m5nU+DA9JwAA8IrBUegAoJWZTgS2nMsNtycNM2pcRzXfibrC3CgzK3K1PIZgBfn6Z4wi6txslXnp1WQW1APw3qQTll8C6CMh/oUA3MZdg9xGS3W+N8yBiDoPqOGQOl/m0R0zYLlM2d0GbhZNcKIMHbzuA6ZcO8UB+TDNW4YbXsyqyC8GZv7Dk4F+GjFcbrgMIy7DDc96skc0DAaME7gx+eM3KNymNxwDmBT6DWrxyQc1YnLNDZ71Fc/6gstww2UYcLvcMI7TkEQzq+uJ2ZPdomZ1jhvm3+tyLtvEfs6doHYopuLG1+euY29dr+lUeH6psmfyJsvi8mSki04PlSPMm13WncSbADlQoM53gvmmTcyVgUidk98xaNMdM+R7r8n5A597jG2wjMBdgbGOTV+Rr8MNzQr0pxniTwZ4GqEuI4ZhxOUyQfxJjxj0iIsecdG3RZFbgL+aCwYYjLPTbadZoAOTIr/oGy5zWU96Kvt20RhvI8xlUuXGDmHEBHMoYFTzyyzmly5TRb6OZMHsn4PYK4p8pytSLtPFL63IgLdkflMVHkgbnR4rS5A3q5w7izcDchtidS6AORAoi4FxbHqVOqflSRQ61jQ5UHfbm7GXLwp8/c11bvoAX777AJ+tlQXig4G6jNCXyVYZ9IinYcTTMAFYw2DwVu6rGfBkrnjFsEB7nP3xV+/V9YMy0DC46KnMp2HA9TbVNZq543Ncr10mBa6mZ2apue9hVud2mdT8WF5jZrVOvHIDF+zikS2SaAXaUjgfqcIT+bPLurN4cyAHMtR5CMheWXur82S6ANCdfBGo+8XmRNhKIb8tzOmnXn9bX9wMgNEexAcz/V3M9Mq3ywg1GAzDrMhngF/UiItalbiex46PRuOm9OKHD7Oatr75DXMao528F3WbyrSqfNQY505PcxkBo9cnOgLze4zICrYwty+WtvuABfoMb2Vm8e2r8gyrJRQ5ylcE2NYAD6SNTo+VJcibVc4dx5sEuY1WQG+tzjdl5QLdpvV3zExgm8RyhzJuhrxRmBN4O+AGAfhiqRjPXiGeuDbAxTgQt2rcWiFaGWg1qXJ75+YNCqPReJ1HrLjWyjBBfFHpChpzGcosVs3TMOJ6G6enLlqYz145XVUj1CLI1Wig1DxyZZwtlZEodKvIfajT9U9UOgudzO202V6SfKltnkj7APgx8aZBbqOl3RJV52DylwCdpGfVdiAtB3a/DDZyL1vJ9wXa9HtAka8gN0xHJ4U4JktlGKEHA6UNtJ5AOzgQd22VcYb4TanpzUAGuJFb9G9zJ+hoNEayEMNcloW5/btpPdU9GIxmhBkno99cmA2h5hW+kH2aZmEOCm9itQDr9GU9Ot555naKRSZMc2yRlgCPlifMLy7njcQXAXJgJ3Uey58DdJqe5PF3StZGoXla7MQ+tL3pFN7ADGyi1JeOzuXPeL8xAXwwwDyWHMPsjQ8GWq9qfNBT96wm4KVxmy2TxQdXwI0keTUDXpfx5O57QGmZCsCgbd2zIh80zGgprIABcB7uSywVoyZ1vqwXqsiBtSMU63RHldN9InXVlBslCjgX3rF6HgDvEl8MyG20BnqwrBTQvXnR8gR5NnkrdmTR0DRGiYdGqiwqfFbfywiWpZNzgriZAW4hrvRWjdsOTu2tWGutWFU+wuAVcO70HGcP3arx0VtQW+5Fj7jqERetMM6qXJmpTfatRhNj57HmVomDwNtX5wbLLfxGw+n03EAdnr3inZRb3NVcA8xs9V1anrTs3LLeYHxxILfRukM0WFYsvxDQQUtFkDc7vPycCmehTb/7dooyrrViIe7ZLVCTN66GcQb4CD1/KmWcPwALzCmYb2Z9UNY07tsFuVXjFPy0LL+eqQ0axozT82CGEcboyQfXgBpAhnEa4DYNSTRT4dM0NSl2hdVWWeBtIT/Derm9304HmU63SSuFbtsQiSLlLZj/AHi7aAPynJXYcgdsEEllvcykmeJlRYEeKiMyP7STtlDfwTpCNsr82we8D/Dp07jWClXn852cmEepQLtKXC9/IwZlMGjjeNn24Vg2Jv9bb4YX0lTWdnk1w5Kehu30tN77oA3G0eCmJ3gbbTCauc3W7oJlMYG5fa3dYq0QdW6w3PW5AbotkKhyO23TMS0VIhnRBKyCMr4I+2RnJuaBvMWKi5VxMOR3s11oGaFyEsrbr6cqpFaKX6cPcAfkxh0vHoK4niGn7Z+ZbrLRI5QCtJ6VccAXB6ahhaP9g8Ko7NMOlaPab7OtMpL0N2YlOn65mk4o4zi3yQyTvaLVAl2jzQbmCtPDtKCJEqdEthAnQF9mK2KtUKVut0NPdU5Dun+1gHdGfacBeK/jz0bGdk2DfM+VllKtO0UPlR4tTwDtYLraEFgpqU7O7XBDswLd2gw+xLVZOj6hZ0vF/ikzQ3zc2CkAWJgDs7WiNLSxslfjRufPMJ/GkvMrk5btWyzjOEy/bfsX9Ty/gNoEYD5gvTSYO0t9iDtAB9n8PtTJNGeb7HWstIbtPcF77zYI+GJjC/IzrDAbUsB1jCKoA2KwB8stvTTLyCfq1CTz/I7OLcyJCrcKXBFwk+9UgdO/CebjYq1MdgpRyd6KndS4vRHIQBuzjCG/AcvzV6wvbiFubwyyd3zSmMaW279peKKZ22PMrPO1cWyQaaEBTEifJxF/nHRwGmXmkSxhoG/8csAB+EaJ+3BPReE+wxaVk79m/9wzzsRBIMmXSzDhWeNA1S6GOpDVzqQHnorItpN2VMXGDIsATqf5d3ESwFuIL52bM/AXNY6JfX6n4zTdXSF0LPhimczTXjFgwIiReOYW4tSG4crCXJet0/2bbwKaQW6MWgg9PaNrJqyZn1OuzNRJamG+XiwA9vVwDNDtUEUH0MbbTh68ozrDn1lwvBeBNTPPYfC+F/7ZWC/8AACXu1sAPw4Cu8gycRKECpLXURSBMlJDyHxv3AG489s46nvjlWsyOkVRiIN44tZSgaPGLUhDVgqAWVWPuJnpJqCbMsD8wuXJA6FplaPGV29dMyVPocmJZFLksyo3w3RSWh5TOwF98svnO0HJyz0M1GqvzDcI2abOxsx6bCq4QLfq24O6s52ADdhpdD8sCvfVB7grY16Otzf88CRgB4SKeocdSjpKYOOF0+khgFN4Uz98Vt+LErcQX1T4TCprqywqfFXB1tqgMPdVOUDGjiuD6zjMoBxZH/wGjes4kPHm2zTL8MalHdP3kapyZWDmF05YME/PJp+eW660mkar6FmZ6xnWFt5q/tRWibvqfFnvFuhW6JPt40N9sw1tUpv/4HhYJf3i7YHcj5NYMVy0GjqWfYB46Tn1vUwPARxwVPhiEVOIL8qcKHGrzK2lYsGtfQvDbKDtK3Nrj0xqfB6BojCBWik+/Qxvq8bpiBe/rhu24bRvufVerbfhqxnetrOTdHoqbWDGeZy5A/FVnS/jETmg221jp3ubbQlvvzrtftgzztSWHaIZyFttxFY7VbgCZtqOcHeq3WtnC4GbzktZKgCvwjd2illtlRDEbSenVeTKQsoqctK8gLUy2SHrKHGrsNc7b9z5Ns8K8a0a5ywWvTm5qPlFEgbKqOWktShyECWegrlZV7MBlhPDJKBnO4Yo743FYlU6gTvddEsk9u9TAbgkDmj/2XiXDfLeG30v9eAWyjWkQz17BbM8LLzJ92yAA6uV4kPc+01tmsVmUXCGGtLPJRnZ2Bbm9Lndo5nGjI9GY1C3WVWvMB/NsLn7cx3louYy1rHly7pidkLrky/fZ1tFEXvFmPn7fOMPXfbFO7cwN4Aizzm3VouFtLVbJoHuAh2IqHG4uy5rq7yxfbtH7HVyqx7oMEcS5Gc7W8fa0xTyseU+w4GQ2C6xoYX0uwjgdr6vwul0CnFqudDOzcUTn2C2gs7MUCTjtolP7cdo1NJeaq+stsOqxm/eirIQp/bK6J0cbEzPOFezzaKIT47ZI7dtV8uJydgVMxPUAhzjtE4WWwUz3Oe7QI3xFfm8febtUAJ0Ot9G0i+/g327VZyNbTRyB1NsQH7mhUvFKSDPhbTuwnUfGzrI/d7Ae/5OAb6k81U4hfgCbAbi1lJRFOLAFtxWfdM/C/HwMlsVrZVhbJW5cVw+B+LuA7S4jk8b8whCx16xbbfLRE9esBYLSOcnPI8c80nOkJc1z02wJ8ll5MpU0jyPAfqy3Pmcdo6NnH2w837dIu6ZZzRSYL9wid5iHGLZLIW3KSa6DAmYi6wVH+Dz/KAKj0FczRDXpB5rqZDyfCW+NEu4QRaYe7ZKCDIOxBd7JT4E0WnTnIdaQdM6UcuyOUp99s7N/OIJ+B2eAIBprPliqczFbdT5PI0CfdmUJGGQywGbpfjy/gTc+BLYxQVdbmWAy5e6IvzIXQ8twV876iQ0Xe6LG+83wipcCnFrnWCdFlLj8AAeuZgAsI4HH2dwL1YLsVVuUJt3ed4WcK/2CrVWuNErXFsU9SfmTs+NKrcLp830EC1FrJQQzAmYg+ocK6gV5vrMVqHbiIrtkM1CO1cFceix8AgYddTwQ8nGOoNXF4mjRpyk5km88SjA58+NKrfzfYjr7TT3zzifvBqHY6mEwnZu2meM2/dmLvB1YD6lcPPrtRwf4mRF+fO48EewBFX5QljSRtg8cpgDW+5SoE+/lVOFb7b7Ko5T524BzDxu1pcE35Oya//H2O5d5slPCFnLGUib37GZALidpsjqCylxBuKLL77kozD31Djg2Cq2o5NOM5jg67zWbbFUvGGGC8wB3yd3Xz5B/7Qzn8bCtrnN2kIbylHmiiyro8pBLJZ53SjYhZfBHGRd+ercaWMI6MxCbaDOZcjxzt/ScbZ3XQ3W3f6Psd077rHNQLTd5Z2bYYAv0wMqfJ0fUeK2c9Py0xt+6KjxpZ3UVgkvMw07zG+1VDT0MvyQlO8dIE7HJrVZsP7mhh5yoZRVzMTesHVTVW6nWYvF+uW29zQF8/lckFLndHE3QPeUuS/rgx1pOcr8Xo+zM0Ro3WUAPg7yx8bpH4J1HGSLBN6AA0uJCgcCVopNH7BTXCVu1k9Pjdvp1FaRhtu5uQ5P9Kf768Om4T7td256Kpb2W6Vu1Ap3S2LbSbp8zqheFjwMc7oYHMyX+RbQpKrlxE1WhLNkAa8mOkKiAXQeIYzYFZIXLsgf4G4bhetTDG5mGgdwttMzpsLtfA/WzugVD+LOH7a/lfddkfZN07a35PuxKHEQn5yoct8T92ML8u3NQFa1p5S5PQkt6Uin52KHkO+sIvaouoG5MhOYfasFcnU+VbMSmjR3C/FAIVGwr5Wk4wH7uohs5Pt/+mGP2HGdJMVfLrwBOcDtb1+Fz58biNP6PIhv1LjyP1dF7wM8tbiAq7i1MjBGudieYa4V/7AsW8b6ffu2ILMBPV/OLHydZaBAXz1xu04WieyqckURDSwwJydUqs6dlDF1ToNYJxzQbZM5Zc5OA7/PikautDquHieEKcj63HfUyhd80hBfrWeo8aR9QvNxAKfTvWmsEvfzSSCOVY1bFTtNc7/nhFXhAzmiXWWOINCXjk1sR6Vw01JBIW6/L1bL/H1R5QswPYvF2QhY1+WaDE5K23FKzhMAXwSdsQE6sFXpfmZJRyjC+3fLoYlroR3K7BE7nnDagfxeVm6nKBqCVaDGQ+p7M4+5fA+qcH9aBOIbv5wqc68cVo3zixX1ye2IFX/kClXliz++QDBwZye2qpuqcVon/eRigTT5vqj1ZT0wqnyevH5lRrIsCxmA+bIO1vrh5wnYJa69ElHpdjlI3jUBs0IYcKWOiy6gP0tImNBo+ctA/gVBuwjQoSgAN9sGb+9nAU6+Z6lwW34M4kFwex2cwFZ1e58xgC8PofKmLZaKmgeDzD+p9RK73Z6DOLVZOH885pmvqtvt1FScKoebhqpvSu8UzEGTI6HON1cEa5nrfF6lg85KqPLkfCakx9ebBb7whJiKc718uVM0hbEkpPXFIMbK1oYA96azEIc3n/PF4ebbqHFSjw91/zMWBqtPvpnn++WJoCAPAXo0SnQ8rbD2P31LxfohwIbQiPjlXlJFfiy/idUytckpxhkZCZJ+M98hP0jbyPLGVHkK7KF0gqg5hu/uJFAA97sYtbI7iKWR265E+mx4+2X6AKfzOYjT9I5d4uaLdm76dW288bStsmRnjjj2RiDAVeVYOz83QxAD4XRuemp8450z5TkdnP48kKudGeLT69/gkZdkAGucxGEObHJMo1y26jwH6ACv0snHmsZfcK8tbDQEvCRq+XGKE0EC7oeNWjktnP2oaacgrwTebLqAGg+pcGBrpSzpfYiTckUQp52dtmxS5sZWAaKWih+cxWLD+uIU5ja4NwQ5ZSLdwSm9QQiA45mv07aPtt0MACcWSxbM5zLtK+Scbc1YLU5+D+LOd0RUOpkZhXqg7mjEVvWBMM1h1a7QJ+3qNmrliwB1QTnB9ZILb++3WIXT6blKPNTuBfI+0APgjgw/XJbHg/fmRiDAVeAE5rZc9pZ7Mo1CnKpxa6v4+YMK3B9+OLd9UeF0OuCqcszfubIJvbNg7lstcKdv/fG13JCKX9I6X8BC3U+yXR63DlGkjq8zqGakudcL9NUgPzWwe7atFtxLOf0ADvAQd/xwfxr97beNU+N+zPkU1y644M5R5Vxs7JS5PAp0LriRKznKmwt3BAsFO5aNMI0P91S5U8i8XBbbjh8tg/lSDIW2nRZQ53PxG1WeVOn0h3/Sk4A90KaikGy+E8A+tJvVAj4L5KeC9l5tKainCby5ulMAJ9+jKpy2IaTEaX5lpwcsFU6Nz3kdcG+XMBqjATRWZS65PT81YmUt24W5/c6p8Ump57Wd8Nu1V2gCTpX7MMc6G3CSsDB3OkFJBNU5KQfIA/qS3vkCdmdO2jDLzMD0FhA+MezZC7KMtgRBfji0966/sD7ReopskdYAB4QQp9NCat2HeCwI0J1OzmW++zvnJiDbwennodO5Z63EPPItqBn4BKaHYtMBSu2U+bd9GfP2jLsNbiTLBtQu/900ntXCqvMKoE9tJOnpcrsLEvtZd1doa/CmNveOoM+B+wLyQ8B9p3V2gTcQBfgmX0yF0/m1EPfLDKlxbnHmNL6FErJU7PC9VFjFvKjweTodTw6Eb+bxn3ToWCzJ2te2cuF3eK5PsA3YPT4xKZU3Cn5Nw8J8KSoN86VI59Jh/e50UWQAfVmkzTIyCQOTsmyGvQCfqq9nnbSKwLrq/4ago5R9o3qz1k8LeDPTmqlwbvo8jQP9Oo+xVAKxqPHg8pbt7XTYYchSsScCiYqOPVclNAxRHL4SX6YDgNcJGsq7nJw9v9wH9bJADMzn2pZsNHLVuZ/OL7QR1EOTs3ebvQEfq7NjvXZd3f8t+o3rbQXuZFmtAU6nSyDupV3S0ekW4qH2U2hHlPmSPEdtz79HGGi4St2CW4GH+VKnV1/qNnzfG7d5RjN9WriLnADfZtkk8L0LtX71wrFYPNU9lbUWs1Xhmerca44I6KFpyIC6nxjxWcWdg0cAfod67+cW/Q51FgkuCYwq1Pcmvz8/psLJ9xyIGx/CNI3/O6a2mWD98sLwvXLLm1AnaOyuTf87bWGVGiehsEI4qMC5TCGLZfObGUOeC3Obh/zc2C2k3Lladx7XRjrN/vTzb5Y9rdZjs6t2szMBvqDOc92i37Gu4uOyBtxAxGIQlFOgwp1yciHuATw61JBR49RWUZnATwX1z+mwQwpzIO/OzqVsMo3Cv3ZIohMKULBDBJlOT/t9o1rt3Pl55/CzVMCcVBtV5yDlIADkmEr3povUdYZajyWp1hCxantBvgDuW5DvBe4zQhvI2vJ7AxwQqnCAhziXnoO4ClgqMbB3ignaBnqukz5vZbFTSJN8Ve4HB3B/uvu9MdAlQVU5icVi2YA4H+ZAhjrHNs3UHlIOl36zTMz0UDl+FIA9lKzRBWIzNV1Ul1dP/1v0O5ff5BgTbtlkXZlgjwLc+82qcPI9CXFOiQfKMxzc/egMdW7Ioa/K6bBD/8o+pco5iMfUeCu7hY2l2Lgqn+DMdH4SsEphvknvlbdxSvw0AKqAzszL8sEzbBg/3gTcvXra3qL/hqCdVWeG+mbLrAC4U54H8E1dPsSZzs1wmyJWCWerVISjCOcYDTaq3B+lQoEuCfbZKwk1Xn2lrhh7hSXLXJvTWwgepiRtEuZ0KWJWi81Lq/PhnAN0ms+fF1ip0Y5Sp5yIzBfG7nAHmgK+DuT3AG5gX3hH5uUAHGgE8ZAS9zs3lzz8dGeaxP9WyO7opM9J4abZOz0dJU5UespWsRF6hgpV5vROTk6dZ9kttsMTiB+8FsghVb4A0/PLF7AKYE7z+Ok35ZE6SXFFQOfy+dO5eXayFOpcokKQZF0hlITfrIry5SB/o9DOql8AL1G5iWmbJYipamAD8dAJg4U+AX3QUgmBWwhqhTKVTv3wqK3inQCkFojzAK2EvVJiqygLymTCmKVCVLkD5rBfHoM5rS7pm8P9HrVbvPYBEfjGlHhvqHOFCKOragf4Y0xYPg/ye4G2jYK1KW5DAbyD5QumZalwIAzxlBIPlM1aKnQes65bDDHkXibMrS5rsfgwn8rYKnq+Lrfk7Z2egXxMm6tCBYYm+mAnvvb0Gyxog0qbAazIN7d5/PxkEgtlZlq27RIq24ti1dxAsYeyHgH3SzBxozgDtG1ktaUlwLn0MYD78zmIMxbIBuKbMj2IE+UdtVS434GTUony9m/ND/1e4b2FOZAeP+4H75G7vzlbJfZbHL6atdOALRQDvxeLxYeuB2c+rwDmfv0pdZ5qOwpsF6eSwHymfLaOUDRS7LGsXeFuGo9aaQ5tYD9wA8XwjtbVGuBAHOJMWYYqZgb2UUuFluVvi9C2abgfcF74NN2FuU1rQzL80EYK4k1HqyiAfe7KRnVHVDmBHuuXR4Edm7fO2MAcJD9IGV6SDZADgE4Cnckjms/UwdaTCj9D5T7QFe6qsrPzbOAGOsA7kUYMcGZaF4iryLxAGq5twek+f3LWN7NtY2qcs1dccK8wn9pCQZ9umOuBJ9IG8nG/c2PzZqGICnczAhu17ExjLJYUzL189mewvjk224pbBmCzHEGgR/Js5sfSePUsWQ8GO1dEDfrEIO8CbaDJaWlveEfrrAW497sJxCO+eNBSybJattuw5KUR1Cf3lTZV5RzMbZ61fn6/4qDLjVDh1LjbEZpYGMba4F4FF/W//d++Kucslg3Y62DuzN+0x64M5yPbP7d12Go3IQF2BtRpfcE6U7ED2LlqQrH/88iPADcgv9wvUd+hfMw0qQrf1MfAmPXEUxB38jOAD7YtYat02l8sX1IwB1agAzKV7KvwEMSL9ljJTrqBNmOvMODmyohaLLkwh5vPmQ8vDdM2Vp0DyAG6XXx2eZl8bJpUOqbOYL2p6AB2rphQ2y4N6+SjkRF0FLyTdbcAuPc7pcKdNCUQj6j4WJ0pW2Wjgrmd27FReAWeei45hTmtlwM6FyGA+99DdfPf43X6kPafjhi1V1KqnFXi/mcGzOHlm2cmrRaQsrzJXJrgNDupVqXnpGPqDdYtiZ3Abqtq+zzyhl2zxe1qBO9kG0oB7qeTqHAvXcz3lkJc9MafRDt6xwJsuKqczvO/A2m/26+D++6r8V2ft5ICdyA2FksrmHvtCKZhfncHul94R6hH25CKxiNj/GJ0OlkklHH/KhtD//LaQf6kaQVtycovVeGtIE7L8iGeiI2lkqvGnTRl2z2lbH2bw9YS9qzz7rb000sgvn6mlyMrQutTtP7dz+QJGjYdn9+ZF6l3kyb2GwJBE8lL60yu4lwOZG6yKk5t2tCOn3mjVhoqbqByReTkrVXfsTJKVLj3e1N3jZ1C80cO1mC7QtOkUZFX+qq3kDK3v0vqpWXn5smOhLLOzhubFlDlAFHWFcrcTmLbUarOY9Ph7uvVKj03bUlbpFFhx4RB3hjaQIszWPv02fZJZF4uwNn6C+wUNn8A4tEOTm6bB9rj+OO129UL6537HZuWNcAW5mu7hIqUWaHcI25jarxJENg5PnkAnms+btqUR2qxsO3IhDmbDjSt95uZFUoXnU7qtk0KRqIMNq00PdOWpajWYOcqmePSpkY+mlhAHeANtFXgQAOIR0aBsJe6rFKPWCZIWCp+dAQ1Df/W/HA6HuaAe/NPzqvebGweopVIv22bKFlZOABFGC4eiJ1RLMz8jV/OpUEC5jaBn45rK9N2ui2ddNimbQr0SDlV6QNtWoprsZ8E4K5bd1BW+0fK+8vNI2xfdjmB6QbMNvbTer83bfBVLwtpMj0GcS4k65FT6kmFvn7PuTWfA19I+XIw9bOH7BDrg8f88xDE+bbxbXXTstWwoQLrUnxlJFnn0ZP1fEUjFQpceSHf3KaNHAdA4PgJpHWmhwSVlD81jClkW1N/3WmbOcmdnSXlZOQpVt+ReSIFzkyTWilO2sCBxELcz6Ns2kI1HpsWyt5YwXNjx/3Lc8nt+TbY2/SZOulnq2BvCgomBq9Mc1X5Ro2TMkqVObZl2HR2UrDNjLpm7ZZAWtG8UFu4KFHelWodaKvYs0De9izSP18PgAMngzhXnwTWXDuEAG8F6hXQbpmh6XTe8ptpYu6zUUIQd6e58yRXDiXB3/3JNHKBLeN3swUDQZjPkQVzv10x3zy1DLQNCOy2ewBdUFY0T24+L2rAvt+dnTXltYR3qry9Ae6lj9o+XJoYhJf0GWo81MbgNEFZwoiNWomNGw+quVR9gXr87109cCAAOQbQEmiHVHk0rauoUzC3Tdm0nfHNN2kBd1lz1HmoDMk8uKuui0r38+Xm9bNyIipQ3jKOvIt/o8hf57xZvlhsPlc2DoI4A94kxL08SYhLIN9gf8hVrJIx25uHVyGyrRJpYuPKY9Ni0e0mos2VV2CJJfsAU0bKMw+mWX677Qnu14lp0W2ZOo4Tqz6LcztyLBUhTutu4N4R3k0AnrMjcemZacUQp2WlIM6V13J7BufVGYO+yo12bgZgHkoPuMBOAT5WZrxjlv9dfEC12qYSscLCNADzQLnVMJdMQ+ZxmDMfBeK1Fd8ag73yzk7UN6wgv3jFV2zoLCXA7Xw1EE9FrHPTaUOhGo9AukdHpmReCuald3ZKIb7nLfrRdSzdZt589o5Pbr9I2WctYc7lCU1D4pisBDpQ4Ea0ZF/l7pV5Z2ddZTXlZJ0xK9I0Bzggh3ik/LXzM9xBSqdJb9UWR6d7DbgI+eH+Q7YARMeKS8eRc/Oa34ZfEtKOTGGwj7td6iLTYiNZ/O9AOB2zDGzHo52dmuY1YROBPJv5sTRwV7l4txeWLS4js5zInZ1lbWlZXvbZsSJNthdXqcL59Pz3pJKJqHKxGpfmi0XlPiO5OSg0woVPK2tQDOKxduTUsQkOpqm0OXlS+bh5TLpimIOm9XpK/fR+m/xp2E6vAro0DQ6Eul9OorzVWmko82vLK/KsCtMUdai0hrjfvhDEhaNGks8Z54JT/J0j7ouHVfDWX8+zVWL5uLJD7Yjl6xoFlpiNqMXC1YGIfZIjTJj2ia2WyPTk8VvBhk1dOVzyy+/M1abv7Kwpq2gFVabpAnAgH+KBtEGI5xwAqXkNIuf5JspeagdVNCB5RnlojHmobRLQSyEehfbS8dl5pUtDospD01LDEpkyNpvWr6PUaolNx7qIbDRU6EChSvfrEdYlLe/Qzs5uPcaJNN1UOJAH8UgdIoj7igxCNZ5SdMn1m6f4JfurDLRb9ZxSwhK1zpVT0h42TWK+2myLRI7QtpLktyfIVGd5YN/rpczZPFy+xPTocW3zSdmRqdKLztsN1XoeyBtVXNw7XJmu6DIsMJ21Unp44imIO+ULL5ul4cEhe8RKgQr2p0mGG0qAHqo7NryQ+51qb7iyvJWnvHXfZDs6zUnsK3vAXGq15ExHI6DnpLP1lgLdr6+Ar3GQNwb3XQEc/HR2GQQALfLEQ5EAepYaPyqSvjg/nftN86SgnkpTNRzxaDslQ5UHpwkWoRnMARbm2er8pEDfE+zrqJXG+2DxAuSCPtaG0vyhHUOwIybVe2Tnjp4gEjt3sRqXHPyZIX00bV6Z/AskwiNW8suXTKuNpp2iS38DBB7ONg37wuZQntizVJx0bjmsZw6vLmaYZXBUi5+Xa6sXtGlsxMrl0knS0qQkX9Vhxi3AXJ5u4c8sZdachXLaIUhbfCaWqnAgH+KCutiyE4qJ9TxTZZa0qUHk3Lkp8a1LR6yk8svHlfNldg3RCVqmykstFnEeCBV2wDdvpc4BobBryCC2DS2UOtOOYx9j21B920gCPHOeCOBM/rRHGEkvgXhqBy89gfhpdhyOyIV03HhKoYfSS+btOrSQi0rlzc5LKvDQ91U9R0eoMMrcZg+2lRlvztZj84JZhsS8pDr3Z3ZS6UBDpY4CkO8K74z0xTZKZN7hEA9FjqKKlZuxLWqtEsNVR47Q0LBDfx433ymycgfNG1dOZzCqvqolaPDs8q1lwUXSYtnUVQbzZPpIu1mYp9obmScCOk0g2Q6NoA7kgz05aqW5cd84fVWHRmCe2EqxZXh5o5EDcanClsyP5m0kORsq1143AcXqy4F4fYWNysnddqX71EaMkBNtTKgEjq9geqZ8mi9rZEtqHgT8EJZTnd6LXO46IPczN1HfZwQ4wvOCAC+FeGSnFvvnge9FHZwF66R1OEBM+M1uPr6sPh55RlucZdhpJdZsRxauhXbekj9SR0OYs3ljZdB5RwK99oo2wWbdDNo2ShveCuC2rIJ6xCqcqYPdMbN2/LwDSdzB6ZctyROdV3nNmJM1A7A5T0BMpW3egZmbN3f4YGye9AYjFMBcMg480jYxzKU3ENkyKk5y3YBO8zRiLWV3VWcngMpLenlS8cotmB/eKWQAlO2QsfQZUI5FyfLv+WyVQBNCXvn0e+uHp4Y31in0dHkpbxxo6jKlg/PCVaIRqfnR+khe6bDEQJ2sZw6mbQHf3M6KtpGbx9VBy/aSBoMmyFmffsGVO0zZLfq1Z5aMvGIF3lKFA90gLqqHy9dbje8M+ZwHULW8mzNWZzbEE2mbRs/tmKvKc8oXHB/iIYYlVkshF5aykcHYFkwszC8DuUJ1Rbn5sy5xUnVy5as6P9yWkdu+Zp2biXqOjmzIJlZm6m7O0si5y3ObIG+lHz6M0Y+afSxyVZk7aovNE0gXs1p62S1AIdBbsFJYBg/yFuD2yxFGM48qdumdo8IDZYk88RjEBXVw87LUeKr8w8eIy1W5JL0U6rJb+fmrgJz0u0btc3ZK9rGcY6wlzIF8dR4ry85rDXRabiuOBsrRm0Qt9seCcpoC/AiIJ/Jl+eIB5ZN92VsCaqas6tvtqYcqTAeUdzpSUHN/6fwCiMdOKsJ0kmDXfUmRkv27ZF+LXGGeFuZHAD2jbHE55K/uMbahwoVh0BDgiM+PX3oF1MweEE/kbRIS6B8UkkfMcnn6PAeldCjiyVZq7+0dBWFHmGdcVSZH4klY0hvoDbdNOcgrVHzzDoQaFZ5xSVrtids6BXX587qq8TNxKHPIYbNqM4Yithur2yBymtJKlafa0AvmoXaEjuNYObasxkCvgnrFblX+PPKC6NID3FKFR8pr4omnIL6nkkqOZOg4YiWZIA/mta96awnxrr0OOdts7yu7o2HO1EnLqVLnNo1wnRYB3a8nc/t1fx559pkqB+AlKhzIgji7E5TYKam6ostSocazFFtGWhIiiEY7KmUVS98GFHuioRT80hEm0XKENyd1D8kJXKLKY3m4316UwryFb87W75fXCehNoJ6oM/zy5cr9q7h3tzJd+uxb0akZa1MyTdkBET2QWkRrjpDmRkd5JMvJUMmhIjLALaqjQo27NxGJmxKO3ldvJMpHSgkWVHgyaAnzvYEOVALdr5Opu+3zyNER4DZtrP4UwFtAvOSSsNAXj86r2WYHDzvkIueNOz3HY+dA/HSdnEDdtpXuXy0tFkkZOXlpvaXqPFYul64A6E12YQL16lEr1SZ/g7RVKlzKDy5tC4hLLRVplNyZt1eU3PTT6UagrPJKIH4GyIe2f8F+VWWx7AHzI9V5blpbP9pBvQjkVQ1ovHLSZ9bKTs1Q2horJhR7qPEThXj/EdwIVNyGVH6pf1/ehHNFiSoviJIRYMm8BTAXtaUz0IF6qItB3sy4b5RWpMJ7QVyc90A1fpJo8e7MaUZKzbt/telideZaKqe7NR84XJVP5SXyhKZxeRPpJVbLGYAOlLE2CHKDBvAG8hdIkLZYhUfKzzo2vbRNIN5a/UguqwVpWr9EeXP3JpekEOZuGfxfaTtjbdsU29hWURXbr/pKLme/PDvMA20QlSktn0tbsTtIOay5xE17V3PzREJ21mwE8VB7RBu6DuJZyudLiz285zP420dGzpViA5iL6t8Z5k3VOU1fa0kxfwCgm171lTRUmEcE8MxOTVG5fjmp/JX2RvRAke6cR3Mo107hpqXGZ/eAbaJckRpP1pGboXGElHs0nTurekhsSednaFoov01faLVEy5XW0TJPJAxaPGul9EyTAfAeKtyWLW6XBOKS+nMslRbRsvzCAzjngVNuPsElWqsoGVEjKOcU/vje+1jBPt4N5qn6W6hzW0cpAxtsn/1fLJGRr0qF27pKy06U08MXT162hkIK2DOpdi+CI/8kMK8BuiB/8Bb+8lrT0Vj11qdzf/awWA6FeQt1buup4WLhriwHee3ZIxPgVSrc1pdTdq0SL4VwKEqV+8kAHYwMm0L8CAD6V5suUTfb1qO99db7SOurx51gXuSbB9ojLpurq5aVGfnDIFeohzctRxDyy5iECs89Y2dMF0FcUlZK4bSIHeHf+y7H7PJ9YBco99MtExcHnuCzVTkXHWAeLMPmSanzROwGdJo/UY5mE7c482aWIwZ4ayulB8RrlUxO/taX0K3Cq078EKrYvB0Vb/RtROIyCjO2ihb7xh778t4wT+STWC3J8rn6WrOVlKfbdoYhu6FNVLitO1JHVtSeQTPTNFPjLbblnsAvAPMeMC+qY09bpcU2atTcon6d1sdXD5gD7dU5rbcxd9u8Iag3wHtAPNTmHFumh6VSq4AksSNzSiJ5w6XZ9w1BTprmtTaOPfaXHvuwVJWHyusJ8zsAeps3BGVEnr8kAHhnOyVYTg9LJTfu7MahnBc1SIC5xxuCnDTBGdu8pxh26EcLi65V3TUWSzB/uPokzBuoc1tPMdArdud93xCUA/AKFR6tq+DEsy1DAHFB3U3V+AnBXRtSmNcAXZr/jFyujpr9K3dfltafA3NpmdJyGqlzUV2xNhQw9pIstDLyz06Ft/DW1BkoswriR6rxnLQ922mE5RsVbKO4CG9jqVB5Jb58dKawvJ5nAhUpXxl5G3PSlgTXzljbSbC7SChvpMzIriZvj3A90SRFFzx+FZEytoq8gcxf6s06kwrPdjVKPEOlV+3PArB39cZPrM73shz8twP18tX5uneppixa7lclqrzQL5/KzyivpzIHstS5qE5JRNisnZmN4J3tE0kBntg4RXZKbTtLLyFbxkksmCpQNhju1yOaqHEua2/l2yNtSTS0WLLrKOWFzVtx0onV2RzqqtWoFZSa/J1VeCpvYF5vS6VajbeyVVJZ91b2CZjvCfRkfTvfxVm1LVruL7mqXFJGcFpl52dseqo8Yf4pTZ46t/W23IXqX/VW2qDCZzxw9RdFLcQr63kTIeqNZCZVrM49YF5TBz8yp3OlZ4/GJ6FTwhwo4kQroJe96q3mEiFHhdcq8cwNW907foQab+qtn4AmB48gEZW9sxpno6W42Pw+kSoPxCEw76TObf01UJe/6q3W38lZQBEQC/PnQrzGUinZwfeMA3lU2yHYY03WlnloJ+cJzi00ijs+M66Id4e5oIw1XRnQbTtyWRsFeTNzvkXHBYnWdko4fWdLZe+D72QHezCEG7iVb55VzhnUuCTOuG/tebV4BpgD1Ve5UgY7IKeZ2vSsZqrwFhAv2IBZvngrS0VatjM/01Y5yxVASTMydsBSoGfnKzkoTrIJmu87Pff5jKvjoivzVjDfQZ3TiPH50kVgtDp7kmh+pswpN1Z+qdd3J8IuN4xRwZtxtmnbjoyhtYaK7cXVHFtlz6c47hoK6RXMpZFOC0TyJh9pO7wyAUG5Ge1cCmu0/WkxzYYfAig787RS4b198Ypoosa/xKgZpx34O6ItbzZaqfKsOhv55al5qXIzy3HTt1HoNBo9/bAQ4D2tlMT8bIgfrcbv1VZJRFLJngGgiTac+k5OGnvsQ6X7f6XFApwA5gcCvQ7kpQ0RLnB9J2tl/lg54mU4iRpPHbS9415g1zL2XuYjtnFLVV5xnBWVnVGHmEWlIq0S6Pkgt5WWArwlxAs3TjdL5Qv2xrvGkar8DFcE9xZ7HAe5qjxVZ2uY1wC9gEMykNfAeylDnrSXJx4tu4Ol0kyNlzwiNDcOtGJE1sQRQJXcnHTo2PEOlZfYK6WqfG+LJVZWap6k7ILywnnzmBt5+XIDeAPZZ6denni07ByI10QvFn0ponFPmH8pSvxe9sl7hnmLq48Ei12Qt4I3UATwnp54s+OypRoX1VdiYR1rSAeH18WGe0mbvAdgpTckxdocmHf40MMD96cqVV5UX2RmA5jvDnQgyGjdFN5LZXnJu3YkJMtse+NPXt0nznPm6AnDo0HbOt7SPtarbyunLi/yn/ia3ZJIWSu7G48jRx+IS8o9ylKRqvEzXcKelFVZfnMP4ObcTXrWUThn2h9qjo3gMRua3thikcyX1BEqt/E6bzSOHEUN62p37FhHt/IOtEh2fxZ5SbSE+R0o8UO3yRHDaI+2WDLaUPYkWHn5qagcR17WkCx/qYcSB+5TjZ8c/odEbedK6yf830PsCeUex0iBxbIXzIuBXhllIK84kzQdvlO6AnIhflKlcbq6JJFgSLFlUfRAq7KVk74btajYfnHP+1sji6W4Hul8ElXqvHD95YG88lKg6YD6xPzuIqu3Gt9VNVWQ50zQkjy6s+njPRvFGdZhz6u9o/uRljoTCY6GOa0nM7/whqD8gv1oetzUQPxoNf6IZDTpSPSf+dkI3qfr5PwSrLSGqvxuYG7rEpYRuSEor6BQFI23rJhfBPHcumoURrFCl6Q5z0F9+HjpE8ap1knPKz7hfp+lynPbUgPzZNnypM3uj0mw2LshKJ0hJw4dY3kP9YaiJ5DPsKznOd+0jzMsW89tfCKxAKDPsopEU16RTUfPMYzWreENdLzr6QyWyhFqXNiOrvXtHKezMHDONjWN3vtnL1V+hMUiTePV2dxinv/a3hCEjip8T0vlbHHHQH7ESaKnpXfmOBnMRfUWRFOQd7MAe41QaXXmbxnFIwPu/GTFxJkU8Jna0izOvK/tdGy+FZg3AXnXgfDVHQV9d7rT2irist4iob6wOPA5SdllSe2VlnHS9wy0tFqqQd5cDbesP7YBz6jGe9crLOsubs//QkO8bc4qHFrUW3KM9hzFIqk/Ei3qLwZ51dlkD198h2h+U8NZldWB9ZzB0ujehnvcVo1fMtNdlSeiicWSk46pv4Zn2SCvvhzYS1GcSY33PlDv0R65wyYn4x6Xqbut0Sl/Y1Ve1ZbSdEyU8jUL5LsNpBekO97SOeioPewy9x4p9YiiOGgfO70qB3YTorl8E4G8iQrfE+KlL4bOmS5NK17u/Z898YiTx5lOnuy+LWxfbef/jqr8bDCXcjcK8t6vX+sSZ9r5H9EkjvTJz+DRP+KOowH/JBzegPzQh8P1tFRi5WdOP/oS0Imqt5OfaDkeURdvZD8IHlv3qspz00YixmadSlAVey9sSQdnq2g9drz3WPRHPCIWb2F/7tnxmSq/Jq0gfGbro+7GLImjhxtObejxotfzKKLHGPLzx6m2UYd99wxXvF1Y02m7GdXhWStZHZs0TyK6dHDG6j7wbPuIR3wx0bPTM1nezhZLSXphtAd5buwBwZP6/Y94xBcVb/U4PAHM24K80wKdRY3vZqvUdFI9vPVH0NhjX9rTXjmjKi+pv/Ex2QbkJXbKXnFkh8qZI+fgKzhQ1Ql8zrNF0TrpvJ1OEV/qMdqwXfUgLz4TypLtrsYfIY8eQ0HvOR7r4z7jKFVemoeJYzzyvXbahis2y1a504PyVKMhHhGNu91WGe1uaq/cIXNyog7knVdONzV+lnj444/YI+7UJ981Wqny4vrrspeDvLOl0jVateEMy/IFxJHq826V773FWzomD2BjPsh36tg85BkvX4qt8iV0oH2pcQ/bq6e90qheLna5IbGwjn098pYr4h522C80HiNWwtF95MojyuMsL3YpyJsH8p0a1/XMd5ZLuJP5kdkWwmOEBh87rpcuts+R++VZjs1IZLFpx31BBvIzjxPn4ihb5ch4ox2dZ/Coz9CG6rjj/eNM9squkdHWNMhbLHhrNX5WuN7TTvKIRxwZZz1WBGzZ9eF9wrqOf9bKI/aNo+/ozDgIzqSEs9qSSPu4w/MLip2EcBzkO6vxJrHHTQE9/PF7ihMB9s3Fva/be/DJz8SkRmXwID/IEz/MVjmDP976po2cqk8Ij0ebZFHdpju52aypT56Ks9krNiJ1PqyVVnG2g/xs7XnE8XG2feJs7bmHCKyzLcibjvVuWFZtnKktR0XnK4xW/vgZla8Ncdt6+OQ5ce/23VuLzlzVqQR7RRNb5cQAuLvY81L2EW6E1vEDznlR45Of1V6x4dWtl4mPA1QWR94I1CF2U79vQI3baKXKW8Wh6+zMNwa99SDrqZ9Hfi8b4wwdndI42UnAqfKM6+vkcZp1tlOnem3s2uHZI7p0zE4f/z/0e2kU0gKCOQAAAABJRU5ErkJggg==\" 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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
        "     <g id=\"line2d_1\">\n",
        "      <defs>\n",
-       "       <path id=\"m8b291064c3\" d=\"M 0 0 \n",
+       "       <path id=\"me8af56d599\" d=\"M 0 0 \n",
        "L 0 3.5 \n",
        "\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8b291064c3\" x=\"33.547375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#me8af56d599\" x=\"33.547375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -2123,7 +2126,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8b291064c3\" x=\"85.522375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#me8af56d599\" x=\"85.522375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -2154,7 +2157,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8b291064c3\" x=\"137.497375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#me8af56d599\" x=\"137.497375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -2195,7 +2198,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8b291064c3\" x=\"189.472375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#me8af56d599\" x=\"189.472375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -2244,7 +2247,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8b291064c3\" x=\"241.447375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#me8af56d599\" x=\"241.447375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -2280,7 +2283,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8b291064c3\" x=\"293.422375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#me8af56d599\" x=\"293.422375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -2324,12 +2327,12 @@
        "    <g id=\"ytick_1\">\n",
        "     <g id=\"line2d_7\">\n",
        "      <defs>\n",
-       "       <path id=\"m9e80e70c4d\" d=\"M 0 0 \n",
+       "       <path id=\"mfb8a265d1d\" d=\"M 0 0 \n",
        "L -3.5 0 \n",
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+       "       <use xlink:href=\"#mfb8a265d1d\" x=\"33.2875\" y=\"62.974219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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+       "       <use xlink:href=\"#mfb8a265d1d\" x=\"33.2875\" y=\"114.949219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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+       "       <use xlink:href=\"#mfb8a265d1d\" x=\"33.2875\" y=\"166.924219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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+       "       <use xlink:href=\"#mfb8a265d1d\" x=\"33.2875\" y=\"270.874219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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        "      <defs>\n",
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@@ -2523,12 +2526,12 @@
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@@ -2550,7 +2553,7 @@
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        " <defs>\n",
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@@ -2574,7 +2577,7 @@
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        "   <cc:Work>\n",
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-       "    <dc:date>2025-02-04T16:11:02.317451</dc:date>\n",
+       "    <dc:date>2025-02-06T12:27:05.365230</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -2605,20 +2608,20 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p60250874c1)\">\n",
+       "   <g clip-path=\"url(#p283ee9b499)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
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\" 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+       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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
        "     <g id=\"line2d_1\">\n",
        "      <defs>\n",
-       "       <path id=\"me3f1f4ffc8\" d=\"M 0 0 \n",
+       "       <path id=\"m4b6667e693\" d=\"M 0 0 \n",
        "L 0 3.5 \n",
        "\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use xlink:href=\"#me3f1f4ffc8\" x=\"33.547375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m4b6667e693\" x=\"33.547375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -2654,7 +2657,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#me3f1f4ffc8\" x=\"85.522375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m4b6667e693\" x=\"85.522375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -2685,7 +2688,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#me3f1f4ffc8\" x=\"137.497375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m4b6667e693\" x=\"137.497375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -2726,7 +2729,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#me3f1f4ffc8\" x=\"189.472375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m4b6667e693\" x=\"189.472375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -2775,7 +2778,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#me3f1f4ffc8\" x=\"241.447375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m4b6667e693\" x=\"241.447375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -2811,7 +2814,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#me3f1f4ffc8\" x=\"293.422375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m4b6667e693\" x=\"293.422375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -2855,12 +2858,12 @@
        "    <g id=\"ytick_1\">\n",
        "     <g id=\"line2d_7\">\n",
        "      <defs>\n",
-       "       <path id=\"mc9cd758527\" d=\"M 0 0 \n",
+       "       <path id=\"mb1b2fe8edf\" d=\"M 0 0 \n",
        "L -3.5 0 \n",
        "\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc9cd758527\" x=\"33.2875\" y=\"10.999219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb1b2fe8edf\" x=\"33.2875\" y=\"10.999219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -2873,7 +2876,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc9cd758527\" x=\"33.2875\" y=\"62.974219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb1b2fe8edf\" x=\"33.2875\" y=\"62.974219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -2888,7 +2891,7 @@
        "    <g id=\"ytick_3\">\n",
        "     <g id=\"line2d_9\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc9cd758527\" x=\"33.2875\" y=\"114.949219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb1b2fe8edf\" x=\"33.2875\" y=\"114.949219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_9\">\n",
@@ -2903,7 +2906,7 @@
        "    <g id=\"ytick_4\">\n",
        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc9cd758527\" x=\"33.2875\" y=\"166.924219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb1b2fe8edf\" x=\"33.2875\" y=\"166.924219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_10\">\n",
@@ -2918,7 +2921,7 @@
        "    <g id=\"ytick_5\">\n",
        "     <g id=\"line2d_11\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc9cd758527\" x=\"33.2875\" y=\"218.899219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb1b2fe8edf\" x=\"33.2875\" y=\"218.899219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_11\">\n",
@@ -2933,7 +2936,7 @@
        "    <g id=\"ytick_6\">\n",
        "     <g id=\"line2d_12\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc9cd758527\" x=\"33.2875\" y=\"270.874219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb1b2fe8edf\" x=\"33.2875\" y=\"270.874219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_12\">\n",
@@ -2977,23 +2980,23 @@
        "\" style=\"fill: #ffffff\"/>\n",
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        "      <defs>\n",
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@@ -3054,12 +3057,12 @@
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@@ -3081,7 +3084,7 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
-       "  <clipPath id=\"p60250874c1\">\n",
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@@ -3133,13 +3136,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:165: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:248: RuntimeWarning: invalid value encountered in divide\n",
       "  angle = -np.sign(from_cent_2)*np.arccos(from_cent_1/np.sqrt(from_cent_1**2+from_cent_2**2))\n"
      ]
     }
    ],
    "source": [
-    "et_map, ex_map, radius_map, angle_map = mod.getTangetial(e1_map, e2_map, [center_1, center_2], dx=dx.value)"
+    "et_map, ex_map, radius_map, angle_map = mod.getTangential(e1_map, e2_map, [center_1, center_2], dx=dx.value)"
    ]
   },
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04MXnTTZrwnQ0sBW/SJ5XQ3uU1exHF/QHgb4Z8K1gZ+plVbpwMXap8x6YN1rRT1f8W1mvojwIr0h1W1X5DJgDZaA7q/k+r85KKdlIWA8IHX2fGHmFaaDfDPvc96s4jznAq96dWepDCfUuoAvqvArmEMpqVTln7xZeafFVPAYdMAfan+J0fTk7c4K31W4G65y1gfyuN8uB58YU2DdOdFbBXQP2DNRbgF5S51Uw18bLi8r38MNB9u3DKyNj5VqYF/uqyBGXIHkW4CfGq4ea8peJDPK7wjpnLWPuOG9KsFeDnht3JdxVYM9BvQPoojofAHPdk6Gdqvzs8ErBxPBKqyovhVgE3+ILIDR54q0P/swC7Ci7aW75OQ8E3dk0+914TUqgVwG+Eu4U7C0vSW4CeknlVsI8GQ8Hc02IpeRDGo+4Xx3xeg6+oyY6c6p8EMy3zRl1DtQ9+HO3h344uymsOXM32+EPBM1cTVFrw5/I0+6SsttmwCvhXlTrOZUulPGZKLw6z8XNczBvipdzNkqV56wF+BUx+iZVPhnmAKPOXb/Oap/mpDYb8u/yEBCO46216hj5HUBdstYxXr26YhPgS6ETFNS6BuqVQC+FWtQwzyl22rdSlXOWjZVfmL2itt4bkARzoB7owPd78MfZQFDPWFs9C/J3gPZI0+5vE/Al1w2AF8Ee91FQ6+pXswlAL4UlcqGWFpj3qnJ1iOTs7BVBcU9R5dw2995LpTrfigpAd2OhdtcHf5zdHNbEebLJg3w6tK+8Jww+f4YCv0HFc8qdhXtBrWdfAMG1idStqM7PgjnTp1qVj5705Iz1VwivaC0H9haYA9XqfCs+TrLi69hyoJwB+cm56ENh3elrzBuC7i7cW8fXeW51P7qvUNi+iMC9FuqiSueArgm3MKGWKWGWUjqiUjFrJz2z1rKUgARjjSrP+QLGwtzVBbLHpArqsd3wAaA7gbpk+hj5/Y7zfKvZ58rztunJTq4Jp7RLoRgF1FuBLqnzBPYdKxKWQizDVTnXb6Z+sV6PKs8p8ZEwB/JAB9RQ36reL6wyPPwxA9aLbt7gsjzy3Jvoz7KhD4Ro9kcTD68FvEK1Z9W6EEapAnpJnUuhFvHlyIfP7hBLjyp3dtakp0aV59qzY1fCHKgDOm3HtU2qli+QHtif8nLmkX0oAa214XnkdwC01lrH2nwDyPVX8DnqASAR6kI7FdBL6nwSzL1pn/isVeVnT3pqrSbEAuhgntteArpr66xxH0+BcX4A43wNBnVi0Vib8sjfCdYzrGb/1dCXfArtVY/tF9S6g7pGpYtAL6hzVdy8EebqEMsdVbn0hh+tKq8JscT9uTqAXp0DIZy0UKd2VXjlwpCH2nonOzWVpoL7zjeFAedd6diV373JOZX6Oiqzil1S3SWVngN6QZ2X4ubNMIe8LRsL1qryjC9tGuPoWHlViEWbMZNT54AMXy3UOZ/vYqNgfcJ+8+uRj+r3zb63xFrGXwl/6VjnX9VW7lP9dKdGpQtA16rzXNy8FuZif0D1xGdWlWvVtvdZCJsMiJUDyGex9MAcaAM6kAKv5h2hV9lIRT0D1JU+n0AnuN8d1qNNezwKwK8CfCXY2Xh31E4D9C513ghzdYhFm6HhrHUFwVrgx23Etb4zoZNc/9xnINwmrZGiAbpUTi0HyZmQnxWXHgnqSer8WQXxSdB+55j72ROfundx5v3V5I03Az2jzpthTsZfE2KZocqbJj17VLs2Xi750apzVxfIj4VaTex79iRgi90d1Ioc+3yMfMCY3hnSGqvdPxX4JZ+s0lb0IajurX0EYaG+CHQp3MKp816YBz72vrhtlROf3lpj5SNVuVKJD4U5kAc6UL4BJQNsVTiD7a6QHvwAVAjyDt+nA/vsiZNBJ2bX5CfXtgB3LdS1Kj0Beo0674B5MB5BXQemCbF0qnLWalR5SaEX6qtgDpS3AeUlaWtCK3H9d7FRY575lKowxnukH77Dl94zxoqbQPXkZzGMkvFTgHov0EWY7/WCSdACzJvi5X7smRAL2edNzdep8mwZAX7VErcV/RRhntsGyEAHdFDnfNzV7qioB42pmH44BNrvAOqZpt3/zAWhCqEAVWBnoT4C6Jw614RaemFOxi2FWI79CFU5Z0Ni5aW88pYQSyvMAf12Nx5npXXUczYD9DOZcjNIa/yPTT+cPPB3i7dXT4RKx0+Kk2rgLqjuuH0AyKi+5mEguzSq8x6Y+/1I4+XeohBLsyr34M+ETgqhEtXE50iYAzp1nqtPx0WtZq2Yuwm5O4K60xdZxvbcjpv7fSPT7lv5oSA94NWhFCBS35n6EtAr1Xk3zBHXC/eB+su/bSjqh70ByDeOow5ktV1S5VybUlktzCXfOWhrY+EcDK9cb3x0XHoUpE+6ienTDzsGdP5E6Mn9UWs4l5snQBXZArUTn1mVXgF0Tp0noZZamGcyWbLx8s6Jz7RuRpVz9aV6mhBLrh7z2e5AU6tz37AAdakOtRsuRSvaCMDeUZGPcjx+InSwv9lWO14F+OseDpIvPhXUcypdA/QadU79NcA8GHsJwh0hltFrsDTBPOefu2FI6hxoC63QOr6TCxW4ZDeC63A/GYvSD+s6HDMROsDHQNPs012Wv9XFyHnVJYZgMipdBfSSOs+FWiphnp38HBViEes2qHLNyyc0k5/SZ6CszoW6SZl3UgH2kt0pbfFuihzH99Viz5rBtE+CNrZT2BUx9pF9zn5AiH1Jsq+cgj0fI4/qMEDnwi2BOo9CLUNh7vdFgHkuxEL3OWijUMac2s6FQ5JjlRlPDHMg9Es/S32VgB77kOrk6mnsnSA9yE8PnGus8PLlBo+Dxv2dJ0Gpdf0C4NomUMv4Yi5kXYxcLi+FW2J1LsLc+6uAeVZR8zBXPfHpfWTqzgqxAPmYufQZ0AOdtmHaifU4e6dUw7uBumM8AcjrM1ea+23rr9be4WagOO9zxyk7gcn0IeeRy1CvAnoh3CLBPKibhEtyAOVhnk1JjEwKsXSnI3L1gXkwB6qADiig7hspAX2W6j5hDEMgfcbxMOacRbN+9xOgOdPsS+Ya6sklL0K9BeilcAsXaonrKmCuSUvsCrF4n4qJTybEkpTFf8+AeW4bwO5rEeqxj8TBBAVe03+HdYP6RhOr5RdLVPrvhvZJkL5L6KYrRg6wkG/JJedDKqFKT+oogS4pbq/Oe2GeiWNrYd418UmNe+KzF+YAacPAnJZL2+h2rgwp2LJg53zexG6jpGcfG+I/BflZ4B68j3cBc63VjFv1SL53LPdRWm8lC3VOpTNAz77hhwu1ROBvhbkmXi7Z1BBLjfrn6gc3gP1gtQKdlknlyANRBfmBNnzSsBeyN5pQBRzIK3xdNQF6GqjPviFUXA91+eRyP3XrrUT1GKDzk56kHQdpV5/CnG4bCPMrQyy1KYlqmAP5G0u8zXdQgLpUJ7KzsjGa7A5qeqYaZ459cfXDMydAf5ex9NoxKkIp3nVlSMW3yah0Duj5LJZUnXOhFi5ufgXMmx7f50InNSmJvTAHeHW+fz+BabJTchA6KyZObTQU7wDpqeuR4xxwDwP2SaDm3lg/2jQv890qCtsVgNctYRvVjepVA12jzgks47j5nWCuenyfWuPkJ8DAfD/G7Geg//VtUp1Sm7vZHdT4BWGg+nd2Vo7xbpOfZ0C5xWrGxcJEAfiWpznZepYpl4CuUOfZuLkEc7JP2jzwLkvgb9IQCxcvr538BOSwDKfOgTqgO9OAvVT/LLtRdsgQSE9gUDn98Cxwd+7baYA+o5vCNZPb1zQeK/vOwprUrctWyQCdU+eZUEsW5lzIAwTso1U5Z5p4eTA2bZohApj7Y+Pq7sc36CveVlpLvFaN31QAebsa0BffbPj0wwo/Z09+DgX2Xc9N7bhYkKWNxfdxEh+1UC9nqxxwCmC61+e3mSaY3yHEUh0vh1DXWS7U4uoDZaADbW/98R1/EyV+B1BPvBnOz1ppHHs3sCdD+qwsmmyeeW4MgfLOwJ0Be/Vj+iZt26PO3wrm7NK6HTDfjxcAFubBd8e1odvi7UD9OuJ3V+JXhzoGHZ9e3o3NWmkYS9cODDzH7pqHrh1X/aP6YQUW7BzUhfIaoGfV+Ykwb7YMzI86lTDfj0/SNoqbu7aAAuh0O1fmLAfDs18Wcad88U64Tgv3Lummvle9nQnuzmMyDdRn3QAK11NPCuLW/igUXxhB4RyVq4GeUecizIFkfXOLNpgHuz8gXq6a/KR/53LMS+oc0AOdtuXKpDqx3TVf/OJQxxBIM0ButbqslcqxN+1sx/EZAuubnretcXPumLAxcNI2gbpWpReAnlXntK1vRkDFqPMWmNvVDg2xBFYDc8Bns/h9jOtzn7VAd22p1WaqSG1G2gzVeiWgB8K5Zj+GZq1UH4TGY3a/lMax/jQmxs6lsQTqW/AVAXurq4N6EegZdd4TaqmGORT+eyY/tTAH6kIt9LNrC7BA999VbC2K/E4x8gFj6QL1CEhPOp5da62cAe7r0hn72s82zfiyYRUgCZkE7Ri1zq417suYtozK5tS53QeiDrU0whxA/bK3J8M8PL6MOgd4oAMi1AOfsWmu4ZGqfBLILlXSo/apw09V1krVwToL2h3H8N2eMC2aIqwCCAqctC8/DCSodFVoJRyqqM4nwNzC6jJZEIFZsgkwT/quyUoRoO58sruggfRFqvwWcejeMQw+dtIxUWStzIH3mdDuAvYJ53BufNn0w6RyrhO5vxzYy1krREXmgJ7ZdhrMQf7OZbLEfWle3DwC5kD5QSCgrNKpP2fCu0JbYFmC/2kP510J6avDPJExa60onVeO4Yz88+8YhunxXQytAAmsg3YJtKM6jEoXgc74IdX2z2b/bIVyoAvmiEDMgLYrk6UA8+O4EfgWslOacsfjMuqXs9ILoSObAuqLJgmHtsXAY1N5PJ63UdyzbwwNfXT1NXgMWRMEUmtKYjFmLoVQgDTThNQvT2oq1Dnppxbm28B4mPtjwd0oBsEcCH8d1KQbTk01HAnRWTYCkFdmswDzjrMxhTcEzQL3TaF9laLvNk3/mdAK0BheyZRxQLdxvZI6L4RaamFufd+Rb3A3lRNhDvDhFkAEuj+2/kNBkXN1Ypudaqgdx8n+vkMmSwjydwX3TW8MQ9r2mCa0stdrCq8IPtRAj9qm6tvsxSTUMgPmIx/jBxBPgPr9JysTpg9XZdQ5UEw39H34D8IXnoP1XVIN7xB/vnqStNJXcbLT2W3AfbObQnMbhZXGXpwILcBbrNcTXtECPRtaiT8TYCKt633DhjBHCuNtG6OiR8EcxG/QZ6M698c7CrkAxcwUdS55zmpV+uSbweUhjotDPJJlQytqCM5S8jfy3VQfHeGaSb7FEIp3ypTlwiuQ7wlJKAURdGmduA0dDgfzoAwHZDmYU2VO9oemJQIDlTmObWGfEcwBWZ0DIURLUAfUKYdbX0pATwTz0EnTN89gAfpYEYB8ljJ+N7+nhGoa+6q26Hptyi0XlLhvV1Tj0bYYjrQO8XMoblcWAdNUwNzkYT5SmR/7SvySdls5r87D74KBd267BDMmK+W0FMFWGzUxeGkGS1fz0Apr3pQf0Xd2A8BO8TtT8Vf6n2Kl/km4IWnKQLw5vEK3+WoEaqQOq859mdnLbB3MmZsHp8xVDwwVYO6OpwTzrZzse/RWn+RGCeigHpc500KxMg0xazMzYXpvQlcDesJCZHJo5WrA1vid0P/MuH21/wmmCbEkcfKMv2J4JbONC7fIaYcMeA0Y6F8IcwDZSVByEFigA3qoO78QymLLhVTOTkM8eUIwZ3eAc8+vpAPkf4B7eN+3S2ck13BLiCUXUmkLr8iQLIVaOJgH0G+FOcjfrTAH5FALUAY6wL57k4W66ys2Cdh3D6lQG5K90umgE9BDQ1gZV6qslcvBXeN35P7cRL3zfeYd8RkLJaf6EIuYhhhWS9qnajz+TNS5qMZpOzJZScbWDPM4dNMCc0AOtSDcrgY6IELdWRHuko3OH586QTrAydVwnnB4xNDKDDh9B3BP+dWAwXfuBn/JErXeUTnEIoVVcuVZoFMAQwI4Qvhy6YmxrxPCLACQC7UASNU5cyDYB38Kr2nLnZvZVNULVPqZE4EauwWcR4RWLlfdV6jkUeBWj6nhi5p5jQWhlrQjFu6FEAs7+Rm1LeaO++qHOucBTv++B8zdsSyp8+MYkYMUH28G6ls78sUp38F59ZxMlQ2aDHx3OMeW+w51WSszwF3j90TgjvOj3LmW77n33IjlsFiNgTtsVIeWlbdz3Verc1Iv/Ps6mAfHRqHOgQjoSMulAyfedJ31gLDmHZ0nvgZu2C/WXjd3iNvHZqS1Vt4A3Oq+R8C7BDzNlzv6l0mPafoQFXWkDgmyS1CvAjqjzulEKJd66GEObPCNd2UWzMH4KKlzfxAyDwTt5exBpQcMunNQ9RDQJDhPy1u/iWoeAufu0Epl+1vD+13APetmOcDYsAhnEdg5qOcmOpO65DMHdynUwoM9TU8cAXMA2xOgAOyuXnMPOrHqHAizW4AA6P54xqEXf8AExR7UYTbdNWNlgkLttavBHJgiLfS6rJXvpLrPuLlU+ms2K4+l1C0NxfhQCFGnUigFzPZ8TJyA2KT1izDfx9ryOH92PXNz+ACgAzrAqnR/7IiJeeRRu+PAvbmdFF9W24jxDMzVp0xiQyvToPJG8C6qly7fhbYa/y0+c92V4uYM4POCMIVZKTZO+5HUeQJiuj0CuwhzGvbgYF5Q5qWXUySx8xzQAVmlAwGch6YcRr6H2EmKf+gv1JvAuffX0nNzUtnqpvDu9TFLdff/Gii0b/B5ONf1wRXHGGDrGEMU+QFeWj/47CBItsl/G++XA/5RV6HMUVDmkb8gti2FWvZGJaD7Mm4RrIL61p4bbPrhiaGW6eHBE8MYJbtiYnZ41spQcCv9TVPeOb+t4O6F9ugLQvt9KZraTNlWfoCX1s8pdFmRp6GWJFbuywWY+7/JRGrNa+MAUZ2D+AcZ57bdJjvJ540zB5FT7bExSvvW6YezbiiDwhi3yZjZjRtPd9ZKTf0/4D2uXVWdXqNAijZLQ8lBXQN0zhenzmNlzZZHMA/KFTD3Y41hHoVagEOda4C+leWhHtQDdCsc3nVSs8UmrP/yDmCuNfWLJQKraPO7hPfgNkOOTY85aJXGEDZJthtaaPNA16rzONQSx83TNgd4SzAHEGa0RLeuINQCpOockIEOJNCWHsAC5PO3CPhvaMOzbwa6GzK2Bhf5d3Y2Or4LvLf2YwF+CrxbFbyifZNZvt9cNxzUkwyWDNC16jxU3BGMab0g5JLC/PAZKnAxPVFS58Ch+nNAjw8go8TFZRPIgWgBh/qlEp12errj4O7OWvBKa9knO0d0OjrL5bJJy0HwPgXcymM+QqmLLKEU3CvGmRtxPQpo/5kBumtjSHtOnVvS77GN+AmHQhh8QDe+GQQKnMI88h0cC+efC7dQoAN+UhRBG4QmhFi2+hnAcxZx+xb55CcN4d7qfYCT/bxqCq3MSE8ck7VyQ4DPvgnk2ijblywBdsZtLjZOy9VAJ+WcOo+VuxQ3Z+vt0C3CHAji5iV1vo2XgJsclRjqVKkHdTIHTwsnr7xvwG2tnXaTGa7eBzlqfLJWF1rBHHir/L4jvKX6A24Al0yOSmBByvcAtIwSD4C3+3Vq2tcjQOdi3tQfB/ok7g0+o4WFebS7YtwcsjoPgE5CLvHTmxzU/XGLrOZpW//nHZT3aJu8S8PnmoYtAJYv738gyNlI5a3wd0uAT4D3yDBN0adkFEpcWQCP8LNhtrMqngM64PPQg3ALCaMc0I9g7uoihDnien5bPj1xqxOFWog69+XcvpE+jgJGiUsXPaPaOVPD/pvZ9NTKgevPDBtrxL+2B4K8M33V6aGTUvsBAO9V313wHvVLQeNTMHGKzESQJ4Rk4+ORGg/8U6CT8lLcG+DgTLfxj/WbvaGUnoigThhqAQ51noRb6IBIH8chig4+A3aAUe2cZZT8H4aJC4ENdNb7ZOe0x/ExDibNAM806wa4sv1weI9Q7Zq2gj8pDTE78cnUoazzdYm6pkAPlTfBbVwH/N8JzJmyY5uBuBQu0nCKFG6hddKDFUGdhl+CemUlrgJ9j9UsayvZicvd1ti0G9+gkFbN+Ia8fLml426AN6jvzae+/nC4NkJe1a5mHB1WitEHCptT3g7IURkfI0/DJJtfs4dYLA9kUp+D+dZFRUZLVCdR31ZW6ACKWSYSKhPVzrYdANq4X+ryJAjf6tfEhLmFIfuX8dH08mVqp8K75ONsBT4T4BrfI8Hd0o5hSBL3pdubYuQIoByHWwIgu7r28MvBnGsb19+6yrwPFKk6Z4FO6gFlqNODolLjvdB5t8f5qV0wmTv82AwCfHX6YetEWdnv7xDgA+A9bvJY6YfxyYZbaIyc1DeMGo9Vuon+9n5cGSKYGmxAilQ4yN+cus8+1u//LqhzNwaEoRRLnrSUoH4cljZVPUKLa1T/O9rpN6OR/TX4KqYfzs1gUVS8CuCS/wZ1XQvwIfCuVesdJyKbZ06U81YpGoMEdcSwjcrAqO8odi7CPPJLYR7Uw3GDOf6O1DnZ5Rjo27Yy1J0Tdm2VCSGTxBSq/1vbGfs+qI8SKxOQn5PBcg+Ai/XfFeANYyxu11pMNyAEPAP2BOpRPSnd0O7wToGdgTkL8QPmm2s5br79fahzbpfpIWRfLoEQ6gAD9qh9zrpgTw/OHybbpGM0ek2WuqyVjKOSDXkZ8Q0AzradCPBueLfuU6vtfpL1RCi4IwXuyyKVHgMdBODETRhjt7uM3kMtvk1l3JzeXFJg54EebCPrsW/bQ/jaR9SQ+hAg79tGvqvM4LQ1V76jTXnYqsOl+snO1o6GvU1+EMTvFEYZBfDuGwfXpqac4UFVOqIrI7A3pDwXVrEE1Gp1Hm0L1XfN06Q80ONDwil1BOU8UGP1zlkJ9jnTqP4zrPeGcssnWAcNSXMOACWQNw5mGLwLdb6NCteAttJH7/iKYxHaJg8GAZ5qFNy+7r6Ni4U7Fyy4Q1dFhS3Wp759PbP3napzZrcSoEeHJMQ0e0MTlLVCNecUfcl6bgLVlhnjpSA+uWstmLPGjPkpFdRa1ZcxC+BCu6EqvOT/SoCPBD2QEkdhgR8qr507QkF2otOG25JYtdtOwiYx5MNtBmaNYt+Rj0Sd+76Z94ICRaBv23io0/rUpK9eFT7xx7fu+7KPzIAGWHCjuKFo1toQ+Oas89hYYxpfLEEcVFknwLc+69rdRYU3h1GkesLf2TFl66VXc3fcfPcZxroPuLOphyDbSL1c3Lqkzu2yw9ClKFb5iNR5VCf4bI6NAdTN3jeOBrmnXhNj6nPWEiqpXhI3P4Dw4+/oZRcAht+savhaFSNv+gmkbdIK8EzbyyA+WIVXA7wB3qpJ0tx2zijA3WcC92O7OdL97FH3SC1EAvSiEl85ONenKFJ17kId8S+JEOBknynYjGGeeo3IR3+5xIcyvntwRr4b7Y8pf00PUOWnpEy+oZ3xarksyLsGcDeAS/U1YJ0A8csALsFbAfJqhR6DhcAogbsHuIkUfAh0Q9pnlfhCAL8qYG5QjL+79lv1I+RCdzWXcplgLoK7r8dB3rdRqvOcwu/wK3c4EFgVNiLz5p1j9O462lc/HLgjgwAO3ADiJZhl6jeFUioAXQVwDbwbjkV2OxCAJE499MPagXOo3J3YsUqP1HdRnVN4L3EdAxpq8WXREAN1buI6EdAZVR4dAhaWInAFyPs2gAz7TH85a0XitOVzVTes94WwZC0hzefpLwudBHCxnXLbtHi4RvFL7YuALpUXAK4cc7IPUJphPtI+SRgFIMrbKdJIpReBLsF7jdS671apzhmgH2EVQwCeQj0Ol7AhkqiOPz7iHcG1M2w71odGuQrjKFm1+s8NgTku72rdc0zUCr7q8sgrHLe2+T1DvEmFi31bZptyvCVw16hzLrRAQw+unQ2BEGaVuLg0A3QHb5uB93L4o9u3ZsLCW+lQFZOdJtw3As80Zl6hzoX6QTs6ILa9rPATfxVUTh78qrXczeu7W+e+0mOlB3lPp70Az/joCaWw7SdAvDmUoiyvBXixL2GMquMXG1MexI2jC5m8FS1U324jCbvYFUEsPMgFJ/CmoRYKeynU4nnq4GnDz7nJTgrcJHWQgzuQ1OGOk1g/OHh8O3V776cC+gY6tc91MyskI1nLME++sbTeyFKQn/hzwNkfEGe2c+U5lc6FUTS+OIBr9oW70jXft4387B+CPHLnzhAQg4LZAqtJIU4Ut6Oxf+FDZajFQ9qVx78aBKj7XRJDK+6LS49bPHEngjcD+2w70r4E6ppwSfUKipYRG41WFQY6EcrDf1kUF80a3qG+qmpnz4J47Tg0sFb4GglxXd1oOzcutn+b1uP2oWQxhNzYvepOUxENgegB5kidO0DvwPaxc/qZqPJYrXsw7+rcvbTC0z6CNRDe+DhlTg8bF1qh5Vsd7kuhdVNqdYVjChBUfa3xjTnnzx+bRui889rpnHXOT7aFVkpWe1NuVOHZtj2/AGrgpCwr9VMN8QxgRVDXKPCMys+GZaTPBQuuS6+6d4BSSPvPAB7k73V3YsnAYmiD/CulJDqwk12I30IUwzr3lOq2H84P2T9GSbMTmoLiDhITxHCMUtWTdj2w16h7709XLe2i9wbwRjYutFJrDR1PgXiDL6lONqSSq1uh0q+EuBrgOXjn9rUqwBo2CR8IYqBOVLoT9D7cAqLO3SaiuMVQC1XnZNvWtdlhFb2AIlLfNJUy2LW4TrzrRZXO1BPqbvWNCG0p57pV1btxaa7Jqnh4sk/Kdrm+T7bxoZV8cRvIW38ZNUBVbQqVzY6hBuI5XxqI14JRAi3QBPFmgCtuJnE5+zk2OvHnAW682wTqEdDTiU5Gna+h4mZDLWSoAY8dxGyk0Bn1LSnyRLXj+Bwfo64URVXd+E4ethFBz26l7XIVoIY9UAl8ph92812FfOe46kIrgw7CCIifHhfP+BzyyyA3RgaeRzsFxGtUuBLgEvBL47XClW7ig+jktz3+DJR4BPREURsc4RYcYRl2IjTKeOHUORdKsTY8oFmw0/2Kgc1AnVPxQRswfhHW1ap5fpK0Xs1z7pnmZeP2T2HfKe/cWQunxk92RqYe1EiIa61DjUv1quLiUXnuWFWFUxQQ56BcDfCkXkadM9tsDAcPRzJwB243kBUp0PdwSRBu2e8GBiaYCDV7+2IWiyFAd8dgL6RhFA8/D1IrAllU3BkV7w+NoLxVuejaeuC/tq1b+eTMrrGiUOPfNexyZnhl3GQnY6N2ZIT67fYhwbhCpZdCKlLZMIhz/jgVnqknwju3P34M0VXj4WSCzz5Esu+A8er7eDDIT1ju28xqgnCLwQ5iSpLAJ4F3nMXi/jNkO23HKHD4rugJQXfdht8/o9KLKj44ZuGhC/rTqvMKwOdCKM2Q38ejjrHv46i23H3mahXf0X9daKWzA5W17sxMNT7KFMo06L8H4pH/KogTf6wCD8oL8K6Om9vwYvOENbsytn67Wc2h0p0aXvc+V/LZKW4AqlCLU98E6HxohYwRCAEcgJvsKwf4ANIDVDzdD5A2BXWuVfBgqtFuWYv3O26nWUKXu2FljL3ZXA3rRqth0nCQj4b4JWo847PVV2tIJTseTk27/mjdVoizKp1R564+MzZRhXMWwJxQ0+KA+k5jYw2w2l1972oc0WcKbiHUQtW5BHS6PQitIAI7gWsA3lhZRyo6mIQcDXjmJpPAm1PmSE366qoBvzcqQr7oJO2851qfFWY5I8QyFOSnKfHetqN8twA+V0+rxolxCr0a4sHnSIVrAC7BOwf8nDnSUEgG/5lNpZsN6NYT24TqnChzA7ChlkCBr+SYEKADRx0/HoR/ByqXKWc/c5AnZd2Az8G6pN45uHPqPRxaWF/YXoyJFyC/+VCCXjsoTABurTWLRDMG5LMOwFnhjlPDKpoyjU+j3IaBEM8BnIP3vs3E7Yp2wPbIULGHMid/e6Cv+8P1O8zdQltmNbC5UMsOcAA+Vu6755S4a45ju/8b6d8pnNO2rLqmZVEf6sW5IhjHIK4Uu2Ibtp4Ea3oMuDa5gQX7Ur6A2Eybq2HdaKX97QZ5MwTf5YAqxlk1ySmV9ahx2g7pNu8nhjj1w0DcxttiX1y7vdxE4/dgKmW2+J2w2/s2gR3cJp2MtNizWDZVbozZwi0GhzqHzYZaJHUOHPUTWDOgFlW4AvBJWwJxDdyT/HACd065t6r2eHdotdhENS5szwEeUKh4puOWJbpHvKhCY6OXD28G+eU/Qzgrwa7TpGwVtfWOpaS86TZOafvPR70qiHMqnAM4aWsSkBNfpd2lkNxhHkDdPbHpUgr3sQTq3I1HCrVE6lwKp3DZKlsl/u9uwGcgnoU7p9qBFO6tqr0D7hKss5COf61wfcU3n5JlTr1LX1QRW8VQmkB+S4jfzXLHSHv8tGpcsPjGU/qsgjj3OVbgDuAU3i7M4qoZjl7R4N3+W3MoaQp14zm8Z6xsHwJ1vve4of1Y/hYP7OmLoTr3fQAp1PdtdMjByDnAl1R4DtKuTaC+iU9OXVMwR9ClaYI0LTAH76RMo4wZYNeGWurCLPJQpmaxlLTIJE5y+/ukG3MiaSi8RynTGXbiTUqVShgbV8YB2X+2ad243HDb6bhCaMeq3JDtxv97tDWgyvyAPoV5LITow0LWKXAAsAarA+6yK20T/g0yaWncDcvshFv3v+mTnQ5We1qjoVAHEihL2+nh5tS7JeVZ9R7BO96WU+2tir0V7HG5ZCxPK+Hu25Q6VUJe9K1uUFlfYa2cDRT52yhtjSr4blYAeHwOZtW3K6dQ9tvzyjvoOwdxCnAy6WkYkJvCFbSB3Ox/2y1TZd22WfcLwqcn7mN7AVi8Dif/Ysv6wA6yFcG656HqDw9mLlwSKPQcrOnxQ0aF75/jG0Ic4onVt6jYkW5Tgx2hxadiqZy9XnNKXID7Nk6mDAghrPjFwG6+O1My45v6ZOdb2s1uEtpJzuRvoKzGo+1sdopQN4H4YlUA3/4NtwPIwvyA+KbMrTWwi8G6P81pzbL/awFjjjjnug3YhVpcuc9qsfCf3XiSNENHZhsr6uMgJQqd/C2FZny7CLxBnQLYOfWdKu+oDGGf0lcthWHi3UzAywBaC3Y/tth/fqBsO9aHOKCM1ar0FuvkjTVXgXwWLBm/hjmxvrUlME+rSGo89RWp8Rjii82qcA7gCcwBLEqYrw7oANZ1wbJs/65mhV0NVj+5uf1nX/vfqxPsG8FoVsux6JU5wL3vKvsU5zEgXxYA3h9gBvAFuEuqXdWegr1CrYsTn4PUejPYhbbehxLwQPn6z/4gvAk7SvvwhyK/q3Fnl/BllkRDMebOqfESxH3MOw/xZUkB7uBN1fiy9yvB3Kny1SlyY/GyBstisa4G67rArAYrliPcsv8NmG3i87GPN8o530Iq0TK57sA6KNLjLAHeb7e+2MXbXT1SzIM5hjCFmQTrGNQMpAVOJmWB2mbabHUa1Xq8P5k67AAKcFaFV5jTq1boVcfSpaGMuEnsPq4DuUKVZ9V0j6pvbHsrdZ8ZBztGCunW/piYOAfxZUlV+LKsAcAdvLd/KdBt0CUQXnvrHi9frcGyx8lfZsG6WLxeC4zZwW4WuAC4xeKVORBltSRq3B5/04MZqd9kYHEdUMDbVLlT1c6142A/Aur0JkGHwgC/GurR2imJWo+vO06tZ9R59m4EhXqH4CPjky0+mwGK/r6fIme+8BKAm24YPTeSM0xStlRh59rGajwod9D2HyMlfkDcK3JsEF+WNQC4/xdHiEUKtdDwyssaPBaD1+rgvf27wXyDuMWC1WD7m6bFrGbLctnVOSQ1vnW6/4voXwJit53CEmQ7p9zjdWQQwZoDuBLqJYF7BtS3epSyOiWujpFL2+PBQgn4oEDYXrKSUp/AC7dvRZCzX/SwUeA6VZ6zSr/sGHvHZpmrbLTtsNZNcsohFVp+qPAQ4o9l9Sr8+JsAnkDdA525MlZsMH/syvzLWLwWg9dqsaxbFHxdLIxZ8HptXnYhvnlz+0meCN1CKwToQF6RA1nAc3CPwR6GU8pQD9S2O/6kbzdM9wMjq9KR/qgo8bAW6lt/RK1noO73twfsdGA5XtCPCvZU2SRhp2GuCHJpJ4aDvRfmSp+Jj6jOrcImdzEO8E6N7+VOjacTm8hC/EGg/VjW7W8wMI9OOKfIV7up8Y+Hwde64LUu+FwXLAZ4rSbMhvl6wBocQA9gjg3ojpB+1xzAtw2hSnf/Hg8qBYCn9eiNIJHGtL881MWHlCiwMyp9VDw9KKc3kNx1nIN65Mf7igfi9lkCe9XAM3Xo5rvzgIwvAXntXYjWb97xHvV6hionfwfAr+2bXEjchVY1ptkWXzBUfbvP/oP122KIH0o7hbgD+NMcCv25rF6JL2ZNgE5Bvi4LvuyCh1nwWhYsrwcWY/H5emzjegKv17JNjq4GTp1vh9x9AYj+2/xbenVHAE8gH4DchNC2lkA6BbOhrhilfpwj5igjKl+r0ulucD8eNfUkv7SN2z/u2jnaE6jHa5JXqHWgAHZuJzi+5a6pWlU+w2oU+Yhf8UY4uCorQKo6xHKyKs+FV9R+NWPO1B1mJb/kQo7zwIPQigDx5/63gzYFuoN3CPQD7ACw2mUD+R5m+VoXfNkHHmbFY33gYSx+mAfM6zipX69l/2uBzye3zEJcMSEiiHv1DrLdhnA/fEZqnIF6oMpNqrKPz9b7dGATFTll4wCgc3Vz5WK7BqgDCrUu1E3acO24QQeNhe13sX18T2AMxAPfrSr9BJhX9Skoiy5VrrDaGwr5VTym88w2GlZx/4YTnMeYKNRpyMRB/EGg/TSvAOCLsfhYXv5v4AA5EML8c33gx7r5+PX1UcxL9/nm0UJczpJ1y/ePvjABNIE7BbvLViEA9veKCOpFle7aUqC7A+3LIjE1COi5uonv6JoRQy/xtYV6qHu/uZ1g2gTt/Ia0juTvEiuM7zka4kn/mTsla9kzph/mJUgOV+VxmRsPVV3i/tArE/yNRLJRk6VG+JurSgB6wJdMZuL42wE6hvjTrB7gz+W1hWFgPcTjEMuXffg2v72eWIzFj3X/ofn1BJ7wOeje1i0l0QtdT1cE8LMU2IA/6NbfAFxZ9DmKuQcTqTG47QatBOh2B7rB9UAn5x63jTYoAZ0r44FdhrrfP+rXfxB2hmnHtk8KM2WxaS+7gQLwtPTDJqBnoCj6aoF5rlw46dSqPFfG1WPqZ/sq1Z9gubVS4r+5h4CCDJUA6BuQj383wD+wbgoeK2J7YcHXuuDTPvDT8sQ/vz7wXHfow2J5Pbd1zV90XAvs8joW44oOliUH27eyxi/ktcHWgVtYJ52BunHvFJXALWzH/ovnaqCzdYXzW2SqBHvXqBbqQb1wczGkooA766tkE689aYyn55FXhV2kM4v4ao0fl2Au+pNgXhoTLctAW+MnO2btjUP02abkA4BHn50latyseC4vEeIf5uUB7lT6w6xBWuIKg8/lgc/1gQ/zwodZ8c+vNSj3j/a7ycYdijbaHhwGBwdfBzu09887kay1xxK6HNRdZgwM7MP67Wz+ugB07GXB+yPc12TdV3483KRgYxPQXd2iQo/+blLp8QAiqAcvgFCodd9HsCH6nDntNcJoxA/gVgF26QNBapXeArziGZyHebWq1d4IGEsAH7SlskoenwGOJVk5/7Seu4vU/FJoMBpWYdW4WQnYN0BTiP+8fG2x8v3zx/KFx173se/RCwarXfC5PPDr+oG/rmsQSwf2DBdrsD62tMTV2O0JUW53GXUeQ99aYF2NB7tddoiv+5fioL4aophx5D8awBrbptCxA92Sr4aqdewrO0pqnCp21z66DrUKfRTQg75L120E9K1NGeq0j6Mdog3gTQnomb+CE4v6usWTnSqgizKhUplH29QwF05Qrg47nrjM+eDaMNuawislYDswYH8wJtp+7C8BkgnVYYvFeeIbrDd1vsB6Jf6xvA6I+/++fLjlsQP7ZbfQys/LB35ZP/FP5pcglv61LkdM3Sx47WNfrRtPOkZX5pbQdeD3n90yuhTqxkEfsOv+q8QB3YUEYoW+Yo+hIwX66r4CtwivG9P2PQThFlcGAMb677+gZcJT50qgc2XZwdLxhiMTX8xcC3ZfIGwX/A415XVWBnnrIBsudDXQBZizbc+GueRTaxHgt20ZVQ6wJ3f18W9oZ60RM0Mko2GROBtlS018eRXuoL6p8098mBd+Ml/4MC88sHpl7lT5r/YDv5oP7+9rfeDTLvjxeuK1LF5VP5ZQsUsawC8HsC47zA+Qv5YD6MtCwE7XSSdAtzvsYSwJxWBbM33/21jj3zNqYY4XX9hUnXPhllhxe3WO9BTJnjLkWjLkfIw/5+BdDXTwZVI5u1Puzwa1vrVLt6lO7zOVOGPWxCAfeWfhfCl3uAj0DHRyaji3bRjMc4B3SiquK22PfJRUefyaxqAM4WFThVfIDcRBw8M7KNtfbtwQJIxzxd3fD7MmavwX8wM/mRd+WT7xYfYwyz4BumLBCwZ/WX/Gx/ZsPlZrNpA/n/iyWx75Y9nUefCLgDlqLrbuFun6Wrdar13dBwt22QPmq2GATt4tGiwBYM0u/c32S2e1MEuozs1qfHVJnSfZLaSLWnXut0XXoMjQCPR7l/K2cGeKQA/GUBx0tA1KqDPtjvZMPTqWk00azwbyswYV91MAe3FiVAA6eyOQvvCBMJf8cmWqic+gn3pV7oGdO+t8XRJeoUHVgP7m6JAbF3FpLW2sswV7yATrMbFpVnyYL/xkvgKI/2J2hY4XFrNitRvIfzGf+Mk4kC/4bd0yWX5atqc9zWqDuL2Pz5NQzGqXAOTBUgB7fP0VLdi1WgNjtv/WdXvoaF0NsC7+/aAW5Ptykt0ReDXAgkOdO4Dv8fdi7NwBHew9nlfn7n4cfXnBNnJKiOqcac/1AwwGOlMn7DjcLkKdaxf7jIsUorQF9q1x9udpEOdMOviMZVV6BuhFdT4Q5t3xcpS27S8tq1XlNtDgm08I43KFyT6GEPdxWuCIC0fKfLWAsQbGGjzcNhg8SJer4mfaBtz9qU+s+IBT6J/4CSs+CIh/s5/4xXwCAD7tA//0+AU/Ly/8eGxw/2nZ/P3kQjjLtn2B9WN5WYOv9YEV+1Oj68MvBWAXgy+74PO1PUHqFux67Wuiv4zZljl3IHYvvVj278ZFdSy2cIt71+gS3pHtYtNQS/K1COoc7KkBN73LqfMYysG2GKSkDuJ6EZhjcI8Eeq7OUYHfXoQ6besb8dUka4Vyle193GKyE4Aa6kWgt6jz6HPSZgbMOeMAj9RHoMItudbIhUbne+QQVaiaE1VOB2LAhlcsDnBvILdb7BgbxN04Vmuw7APxWSTRwEpQf+wq/addif9itv8+YPFhNuH7woo/2S3s8sM+8A+vP+H/W/68Pf7/2GLwPy9bRsxzn0z1/Vuz56VvsfWv9YHP5QC5XwpgXbAYi691wbL/veyTqGY1eAGBOl8BLLsi32ZWrZ/7DEIta0hDCxJqWdtgDkSn6P6/bKjF3azjba4uBbSgwHPhlsAHwu0qoJPxqMIuue0Iob75UoJd8DfNMpfHvMnOikFk+xTaZSc3mXbd6nw0zDloG4UPGiqJx+QHzuz77jy+ZpLQi3RxuTuFxdGZ/5jGyOlX6N7o4+C9wAF9wWpX/y+wPeDzwhbaeO1x7XX/rf8iO+YmOh87xH8xBh9mwQMGf7YrHvhn/MX+O/zfy39I0hpX/Pn5G/60/MCfHj8CiL/2cMqn3XLSP+0Dv61PfO2ff1sf+DIP/Fgtlv03xQKLL2OxrAsO219osS7bnxvGN2G9+sFvYF428FuqyjmYw+xu62HulXHy9e5tOBVNnUftJXWeKHDOb055c6JKgnVUnq2DsF44aKYMFWDn/OUs56aGj4zNm+yMjfOtVamZ+jVAb1XnEsy9LwHmcXkTzBFuc06PB0D48fvUtOgYsEaOMRsrj1W5uzHY4830bnLOPy0J7Jke1odXDHY1bkz4rz3WTHma16aM7YLVbGD9MC+sWLY4uN3CF+v+L7Ap8QcMPvDAh3ngZwMs5gf+af0rPswXPu2Cn5Yv/MuPv+DvfvpH/Gn5gV/Mjy00YrfXw/2wzw3i9oHf1g/8un7g5+ULv61P/GaeWMwTX3sI54fZ4uo/zBNmteTYuZvZHhTnYG7tvn07fhaVMLdbBkwVzKPT54BzAeZx/UhVu1MkGzuPyoAKoEfndCnkwtah9aK6xTLvsxLsknXCWjJrzI1i5M5yO5sB0xCgC58TKCMsS7bHSnkgzI0fRwpzX7b7pTDfqtH/p9vFY+YG4Cfn9o1kbE6V70/HY1m2WDPWTaEu+1vsX3so4uXDE9vSs8v6wLJYfNkHFmuxWIuHXfFhX/i0D/ywzy0+bp/4tC/8MC982Bd+YMGHWfEBixUrgAeWHeqAxf/yl/8M/+Yv/xH+q3/xr/Gf//J/4T9+/qNPX3xhyz//1X7g0z7x6/qxZb3sWTK/rh9+YS8HcGdHlk30o3ZdYJcN3CzM3UNC7gCbSmW+n1RVypx8bSqYuyYc4JUwB6K6nB+EvjThFlfP+6flTJ2gnlBXVUaLmIcomuFeaVzfwJ1i5M6kg66s0wV06U4fQ9mV5bYPhHnsl4U5SBkdMyph7qCc3JnIP3ZX7nYDgYuV76zalXkYK3/t4QezrBvEH3uM2f1rLBa7bEDHlr3yiQd+xZYX/tv6gcey4tcd8Mu67oAEsH7hZVZ8mi98mu2m8df1hf/j6+/wP/2P/yWWL+C//+/+Z/yrX/5P/Gn/0j8t8Ktd8Jt94Ff7xK/2A38xP21ZMuvXkae+hjnn3tYn1sUA+IL8wzaEubUWywIfZrHAFgPf3x26/Roihz344gmmTfBJqnV8VzEsiWsKc98tBX8O8BmYS9sS5Y60DeJ+tUCPfNGxJfUYf2wZMnWCPiRYub7rQF/yF1sW5DPvMqqB5u6YXB3hLpwNpUAGK/dZUucizONyAu1gbBmYx8KYhXlcRo6JGuZkg/dKC8i/Fkd+crA2wB5i2d6hue7QWmDMawP6rtKNscACfK3bv8tqkT0d92jFCwte1uC1LPjEA5/mgV99KuKmnldr8I/2b/BvPv8lvv5s8S/+V4P//be/w3/753+N/2D5GwBbdstf7Qu/2k/807opf6zAY7H+8X93Y3rZ5bhpwBUdJ8hq1x3UW7joYew2u4ltHmAx2/ezLBbr9j5oWOMxDxgDs9gj39yfIO6Y0j/3F0cfn/Qwx/E1cjCHNUmMPAG3iS4h5jpLfAuCJAftBPS0L+Ym4v0EAyjUcybUF+vk6glWC+ZaIy+WmAdtzrj+ijsrQDspj8o0sfER6lwTN4/LEj+IoBrBvxXmdL8lmId3J6e6SUer9RN1WMz21OJijzQ6A2BdsGLdoWWwLNgmOleHrQVY1miCENhOxS8/kcjZumy54p/mgU/7xC/2Y88x3x7dBzbo/mo/8PevP+P/+fz38a/+1f+Gv/4XP+E/+fgH/NVa/C1WPF0sHRYvu2W+uBz0Fww+zAM/mQfW5XPLIV++sK7bwz9fWLYlds2KlzFYzILn8sK6v17uuaz+kX73Ug1r9nkC49ZuN3ua6J5iaI7v1W0PYiLuJInPq/0L9aERzo77axbmW11K12M7O4kpQJWrz6pvzj/TrxtW0ld8XcZ+wLQh9QK/cX1fkSmvrTfb9nE8zwZ4zqrgnoO6UDYM6FxdDs7MyUsTTlwZ94sg6H4AzIPJT18lhDnNbvH1yBvnYZ2TFOaw8EA31iCMSGzwBoU5a5uucGrXTYK6WPan3RbG+mX5xG/mA39dX3v2yqHEP+0Tf11/wj98/Q3+/utP+NuP3/Cf/s0/4MO88G9fP+EX8wN/MsfN4mEMFmvxgf1JUrzwk3nh07zwwz58vHw1Cz7NA89lxQuv44Ehs2I1Zl8/fYV9GTyW1a/Nsv19qPIN4u4FHNsXuh3R/W+z30CT8+2gb6C3o/PzOA1TwFuEME/a7f8TJ0AjmB9tglNma6KFeewf4fbAF1PG1QUQQpqBvliXmtBOrBfbDLQKfeli5LNYLx0AWiWCOwt2DdRHAp2py4VafHtGxVTFzen+MNuqYE72JYG5+9m/ZGDu1HcEc3o81gUbzIP1w3mYu0fg3d+rNfjJfm2LXZkVn3bBz8tje3HE+sSHeeGvy0/bhCWzpO2v64d/mvPH+sQCi5+XL/xqP/BvX3+LX8zf42+XL3zsbV77aLYbxvEFPMyKh9ni8W7FxfjJ02MFx2Uv31X4XlZS5cAObjfHYNwxdHdyQsMsyHQhlvik8SCOP2thDn6b704Dc4TlAF8nUdtxf9HnFqAn9eN2TNusKfg2ylKQz4I2Z6U7IVdEwF4F9ZFAZy6mYuycUSNxmXcb9SXdKOK2CcyjLgEFzOFuFAWYGyuHWYA982IJYG7tArtYLNbA2nVfApasHe4WorIGT7u9Oei5P5izPbyzrZD4WC2eew54/Gj9lvu94HN9YLUGPz+2m8Jf15/w968/4RfziU/7z/jTviTuC9t6LJ922fPZtxuMy2Gn5lZbDLcd4IbdxvOy8Ev1vgi8Y1V+rI++f1/22O5/QQXq9aCdNdEjPZnrloZRxMlPBpgceLPbBsBc6jfZHrfnPnNtXD2kdV19QKHShfZX2bXph5KV7opuU0mtl+7GzJcmhVQkUMd1OSWeU+cBvGNwg6kXDZ+9EcBnd6fXibuQHSh8Gfn/6ursP/GXraJZ9xzzZe+YxsyNe8qTjNFgg7m1e8aGBbBPDK4LrLVY7f5EpTV4rAtey4qHXfFaV3wtC5b1eAHF8YLm49Vvztw7PL/cuzyt8WmDv60f+HevX/D/Lv/elv9tH/iz/W1PQwxXT/xhH/hhH3hhG9OLhIEc3INVG8k2vwAY+ZYWY2GNhd3TL9lYuT0EuKVflo+NW1IonQyyKg+VCvz3lJwgweetXQB6QZCUYH6MMaoL8D6Rh7kbHj/u6DPXBnLdYhuuvW+UqTvZiqGV7I4MNBsflKRC9LkAdhHq3B2VbCvFyItAJ/XEcAvdhxjeHMwRbaf7HA3zcLurPaLOk13KwZz68goc2y1iJeTZIe5yn/2cnMW2bdkAv6zAy+6qfIe6NaE6f+0K1gHdrFvc+RMWj+URLHQFHMvfxotcOXsu6w7yJ/76+gn/YP60xbvtlvHygVegsj/tEz/sNpH6aZ/7Q0jGg95ZvLQAtcVYvHAA/FU4sY053uwTTjY64pEvzRG1VpWb9hBLzeSnBHOtshf7ievEZUy5pM4BjAd67Mc3VrTpMdJfAPKzoM2Z1Ld4HRTALkJdQ0Eynmqgc+BmtlvmRBPFRVTgrnvanj2P9/8VQy0amHtob0rSLtGV7yq68Mo+ZmsBs2xvrjdme2jHrclijIVdtrG91m1ikAJ9MRafr22Cka5aCCCJjQMhYF29H3jin5cPfCw/+7cMrdbgh33gl+VYKRHYFPcWann6iVX3t3uEnyr0lQm/xCadvpsij8Ir0d/h07nRnZ1TvpIq5wC1j0E6MdQhlrvDnNl/NtzCtY/a+GpaTo4Ge0YTPJvhPXFQQbXMXTLcKPtvgjpzJ+ZUeCvQA0hHJ74G6Jl7UPDreOPsHmrhBdbRbhfXLqRizNbR9vexHcv+mjKzqUIYHHFza/ZUxC3ebRbr1bk1Bm6lFWvX7YZgXZqi3d/mY/EwFl9m8ROFX3sc3RCQ01OA++qfe+YIAPz6euJj+cCCLYf88/HEr4/tbUIfJHURgH9c32XAbGuvPP0aLNv2h/8FsD3if/wSiNV6PDYXJ6evlAtupu5vf14IXxrcd7unMCqMCvySKo9DLMH2DPCK/eegOgPmwrYWdV5sWzIl81pMDq3MVucl/5md5k6GrP8aqGcIyUJ7L28COt2GqA3hIhtuqVXn+04EoRYHerd/FCi+TSbUYpBX505lupi6OW4mHuirhVks1nWfEFzW7Z5gNsVuACw71OmiXNzr2bZ9sB6WLk7+Y33iL1/H2uNuUa7P5eHj5DTmvu6vjnvBHBC3D58Gua354gB+ZN+EDwmlqzs2m3RO0XJv/gC7T/ufkaLnfEefWVXOlUeAz8XLs34yY5sB82Lf4NvQtkAD0CfYuS+WqDFpTNy5WFLtwonPQr1CpXNhlyqgI7MtP4Q56twpclSoc7MrwiVS58AGcHJxU6DbdVPrZr97GABmWbGuDzIZeMDbffb7x3zpG/S3No9lwfPxAr6eyVuI3MToz8uHzxOPM1Li1RBf2DNiyBK3LxvG5ekCYJLRdMuiJRMlhe27iXAKfOCYZOXaBecs018M7Uw/2WtZCdzs+OKySt/ZfciNn7QHrgW6Kmvl7AFmz3Ml4LOqnVXbCqgLKtz7vwrolq/jt0XQhnWTkjYEOBXU7kLVAh07lA0DdA/xfRxm39E9pdE9sm7sY7sxwPUjQZzsXwR3p+ot+T6XV/jD06Ub/rx84edleweog/zDrMHyudv65Eu6TrlN1yl3kKb/Ssq8+jk8BVA05sV6SbDkVHlufArAt4ZYxD4lvxLMkW4v7hvTJramOPogu81kJ7XcOETIS18Y47ML6hqVzsA66EoJ9CSEI3TPhVviX9JUdcO4z+6hDyHcssM6eCm5FYBuSfw8BjrM9uSNCf+zO+ytcTDf7hrG/0sHdex7oMYj2LvxHuEep8SPU319bCGRr+WBr8e2dO5itod9qLmJTfe2IPfmIJ9zDgfqJVDj7EszLEQl3vxwdS3cC0q+ul9t/0oYV8fLGd8qmAtWVNYjfQ22usnOs0CfOddyd/lwg+xTVOsaqNeodPBl7C4w5dL9hpbtHD7ASConatzV27cfKpwAPa7rQA0cr3ezgKjQLQm57EA/oG6OgXNQ3zsKwI5ju6FXuQmK4JX8svoUR0uAuu6venOg/Vq+8PXYwiXupRPL/jQntRcFNYyf8HT56k6Vc2rcAnuGzhFOcdtAykQbFWMHRAg5HtMuc+GVrJqOAK9W5ZU3pCEw5655qb2ynTRW33QCP53/a5/slKw0Bub8bo2Tx21nQF0VdmGGFiv03G6cCvSgXTmGvil74wcjQp38bYGjQ9cvUd9ucNYdH9f3vo6u3f8DgB9HUsqhnB8GX/aBn5YvfNl9Iaz9/Z0U5i4PnMJ8A/imyl1oxdrwYSRL+7JH3xTi1I7t4K3juhTBxJyzarBVwldbvynEMrB/dhwD/DmfvnknZ+N7fNuTnbNhXxIipbul+ygpb84HBVfchqmrhnp0QjD3h3A7aZu5p6iAHo+/Gei0jAAdAB9Dd505le1uLg7qTlE7qJPPyUGjgN+32+Cz87u3sduj/tub5o81XX587eGNxxH6+Gl54WtZ8Fy25QCW9RHkqjtLJjP3sMoGcxNA/LUufhL0tQPe/0eOmXuTkrU4vhB6gtIhTIB70bSgkurt29WqvHJM1apcGmtmP2fAnPr2bipvMJzx6YdXq3LtCaRpVzhgrAIn7TRqPQt1xHWJL06l53dBDNXHdZN6CqD7C8/Dk4CSlhHuBFkupE0O6n48hrwogQA7gHt8AGLIkxuMC5Bba2GWXZ1jD7U84MMa62OD6mtd8FhW/LS88GNf2ZB74AiIVmSkIZQd6C6cEkP8tYYhlyDMQkMsriMbqXXuyh0ZcqmxTIw9Ca9U+z7aacMuJdCqbxS9MIfcXmMjvs6utVZmBvKLO6dU5bVwz4dWyvVEqEcnCwfn3Pa4XAR6xEA10Gm7BPIkNupUOrlwRZUOHurW9RODfe/QRCGVOLQSh1w80Jc9b93C/7e6VxYRczB9LCse+9/GWLzstqqhGytV5iuBbgz1l1Pm+7aXBzuC7JVDhR/vNaVqPBhm/BnHPr2tMcCsVuWV/tV1OtT1HUx8IOis2dbe/hPgawCfIaQ+tFKoF0M9uHuEdUtQz96L6M9XQ+o7MMdqO66HtE4MaR9aARDGtm2k4Cmko/2k8CXtE9WdxMWPuqJ6d2Oi+2EPdY7HNggH8HV/ivSxGDyWfaGuZfXLAWzDSEMsQAR0G8bDvSpfD+UdQ3xdlyi0wqjxAOjuv3bZdvW1rLYeEAumDrHU+ugc12i77hF9rRXO39JPq+NDwbcQo2gBezPUiZ9EOSt2I1bfidqOoc6MVwZ4tM0gdOKg7gZAQGzIGOhKf8FPBwr34LP79wB8ot4N9iV2CdDt0dcKwNoFy/4ausdjfx2dNXit1gN9U+Xb06D0mNOlcsmhTaBOVbjdwyw2A3E4iEtqvARvC2gfzx95vdaq6BbV3Rxe6QFqTT+V7WfbdY/oa007DuZ8rs5koX5awd4DdWYY8VASSNOyWFmjsDucSnewjn1xUIes1J0v2sb/G6tnVxzB/bgxMHA3W5/bLwjyyrR9xcUtVcSBcvtveyXmntXywJbZEi3a9VoNFpMqcrqoFRBCfPuMQIVboAxxawi0C2o8VuZsPVKusbtc49/JLoJ5U4z8yp9q4nmaGxMVwJk7ruhH+nKYu7TA/0y5AHUCVy4cEvhWQJ0Dc1XohXTIATpU49FdhII92F741+9M7G/3SYDuIG526Nn9SdJDnZtNoj/W4wUWy/Zu0WXZV2bcY+UGx6P+3FIAzuhkpQc7QoCnf28HYpUgrlXjGTNuv5MBt/tM/F9plbCsCq/0qvKLjFXkdx0soBtbS9y8JaOFo2pZjcvlAdSF7JfLoE7GmmxHAey7yjakfgnuwfZYvRM1HuSvW7O/58Huf+8N7dEWWMKsFpflYo5/jQFWAvEc/tx3EGajyAD3MfESxEtq3MLftPx/zODi8zr5zO3Mu9tFqvjK/u/5ZGeNMVdZV9yc+BThrry7l9W4XG6iFY24EAwFKhdOqYU6IIM5AS31R7dnwO4/FuCe9Bf/EqD77UI6CzleO8TNDnH7wBFqoeCzwMtsOeeLoSsw0sW67LEvgrlIWfjEJgKwj4Y4PxDDn/vxNs11PFHRj7Y7K+WzLFTkAw/GiAOrOm80/RSUd9Kf9JNLaM+6ZODeBXYpBMO1p1CP1bdzLEA8q9ZpJyWw0zJBdadl5jjOCAEfhm4I1LGB0qlxY+3+7w7GHehcqMUtoeuBvrhX3W1Slq7fEhxn92uCnKApzI8dSACOYwxVEKdjyKlxdptJ6zB/c+f37x2S72DqGPkVX2ZLnyz8c34KkG+Bu1a114BdVOsWCBb2igHu6wgKnmtD65OB1ICdjjmpi+O4BpAUVb05wE5THiOg7+9Y2zp2i2bZ/W1ETKhli6wYdyc49nt/StQAySqMyY64/fGAPuDtj0EAdwJwPz7IEA862f4ztD05oGwYJQPpYC80Sv4Pu615Rd4F6iu+cEGtV8fQC5DPTo4KcFer9rSp2CaAcFJWAXZBfbttLKglaANZICPeFv9SiOu7cTE+DniHUN/CKke5e3H0tszArs73kIoDm1fn+xP822JgB9C9LwL1eHc4C77jCN7b3xmAOweSEucgTuoZG9dLxxK0YQed2dZhvztFf9Lxo19rPkZ+5y+gZmzxT+NMW20MXR0/F+qLdcNmYRtalgM7/TQC7HQfuDZksMGkqAbufoxkXLE/58vEn3fqW3u8xGIHu1fnsIf63gfv1flitnpOqDugG+v/DUI43E2LWJgL7raRY8+EXRJolyAebdNCOlHnzPizYZW9n+CGQf5Ntp9o3/FGodknWqf5EX1j73n0LHeVVcjhnhi6eOeUuyvWy7URwW7D67tLsSPd7v2atJwFNWnHqW0w27w74jcIo9DP+wyoV9Ig6tzFzh3Q3UTormztYsP3jdIbRgR13y8UFgEwfSQ/qhN/pn4yStwfIwnacciF+7u0rcVmKv2Sn3uiSWWtNyUh/XDQkZh1QDO/cWvGLr6IWegzC/nKdiq4R0Cm4AVSVZ5TtmFZCHZgPxax+nbtW+Ae71AJ8FG5cWX0nsNB3f3tGplDgXt1vu7O9od/fJqipQ8SkXG5dqSvI5fdpuONLH5K8/ib/EuBHm/zn12XSojbDMQlNR4ramJaNZ6zEpikm8xlKjvTr2pMzcK4rZ2zZxW073Knax1HdPGV9l0F+oySHxFHz6lwdjgR3Ieo9njMWrjTC5MBuWpClcLVHOWuzBrALPCx8S1/0G6f3fY9Du7SEbE42JPMFhducT8ZXiBqPDqAjqsZmEshDlGRx3WdCk/qHvVZiMf9xD65MTH1amx6WKXTryolc4Q1+Bx1wzoUeYfDO8aoqrNXqFHlmu0j/ztbus4L94RsXU6Fb2OJtmWUuaufL7NCmaDc4x2I/2YAn42hU7C7uvQ/t5s7kwN1bs3+jlDr3xXqlbmT+h7m22cfbvF+ZIgn++fLwZ94HNTjehEMWRW+t4snNmn3OdDLfaVlXWp8JjgjPwl7JrFoBuNG+szGyKcButdvTgm5KpV9qDNZyBhyoM9BvgbwCbj3ijEHEp9xnchPrM63MZMy5zQps0nZVt4IeN9+38QB3Rz7E4ZT9n9Xss1gi4mvzpkN6xJ17m5YLu98C7FssjV476gbWLTP8k4ylgM8hTezPYGz30aGwYE39s/2GfVVGnNkufZ3CKtUqfGefivazuBq2+qHVyvwEf3HIFT6zE54Et8S5IcBnqmUwJ1R70W4U+ecenflvYCPfNDJVi68YuO/I4Xu1bmHuIP9DmTYYCLUq3P3qChV8/vfMMx7R+nx0SgKaiK4KgG+/5tu64Q4p9Ar6sX7ld2mtSuEZm0/F0McGPxk5x1DLM4ScVE71lit5vrJnnw2S2wu60atymMQM/UkWPux022cQiflOcAf5TYs92XGb0v8R/8G4HbHQgA6YnUOp/L3jizCvHMCb/eYP82GcUAHDpUejq3uREpSCOO/OSgz5WIoJarre6uFeE1IhSkrxc1VajxuWwnUEWp8FMRns1GVfjh1EL2+laKoZR/awi0Kn1KdnJJndpQFPOO+6kbA7HML4KXyJHPGt3HUTdW5oW1NyHM4FU62cep86zRU5xu89/4t4FMVTQR0p+oJ1P0x4NJXNOeNBKwagEv1wyGOgzixGSGVrJUgPUH13wriBR/3f7FEyUaPg1OvmmEUlDjjnnHC/HLwY7F8Y5uqeEmZ+3H21otUd7DfGZWey3ChYOegLoVWXIw8VudpiCUGs2W2Y89WMUTl81APjlESi0BqrDoUvjcGdCqA0/pxvyMgLvngyuJyhfW0zfrK+ZzIvy6AV7ZN88gHgPHOIZbYukMugEqJ+75KaiXXXmozE/K0bgxwzl9GxWvj4xzUPbgBFugBwIEjxOJcr6QucMCaPBVKge7fO0qXy8VRz7kI/0iPI2dZNWmFeqMAnivrhHhgGpUr7WvBV0mNV4VUBKsZT3X7Dr+SXb9o1uwnRAtrkLbu14ywS8mVFEpxDTmAdENe8F0Kw2QBH8M9gHj8eVfEYIAeutq2xep8ieC/hHXsYmBWeSGuGOjbGEJqBsdG+T3Hx803z8A7KGeAWqvCw7IKiAvjHxIXF/pW1ZVMqqMZp9aXpm2DP611hFbeRHaPHqeJTnjtMLTuFY7k8IvggFHcW32OAggGa7n97VDowRjdvuzbclD3IY4I6NLEp91j3z5G7uAfgx441LkpAN3t177xUObCcayxBFAZeJO/g+46VDjbTwnSAyCeWCfE1ddlLcRHq/DBWOLf2dkJv3cKrWgsVN8NO2eEBf+5vjTuCg6yoJcc1Ch6D2cGAjUAp9tLUHdFVKGDbD+6DEMrBlvuOK0rqHMN0IHjFIhDK+l8geLbZA66CD3pfqEBr0aFa31pysGUM3W0gG+GuHab1L4wrmy7Sj9qY/w8NWCaAua7wp6FWbu77eLWOzAaSZeBNZBR5oX2udAKkFH0kZpPAM/AnQN7AnU6HFfmwyrW98WqcwpvGh93at2m6lwDdP9rgO5SDHY36FKwPLYCdFh40/7VQFaq/cINRQPhZohz485YD8Snh1J6WKds+xZZK6NvJNnra2RfpmHs1qqu/w16mYoCfIP2gKjOubZa0Gcf73d+ImBLYZVApbs/SZmB5dV5BG9xIpT60gAd4bi4FSAp3MMDyGyTAFiqJ4EuB3CgXoXXlEc2BeKDlXgrxKcBvJE/QmilzZmzu4dWZo6vehI0tgr4W0UHGuBXwz4H+kSdk3IyXg9f0ibuLgBt1Afh/gFziySMAlpPSFOE5esf/YVATwBOj4WJDlfr+VAAmCr8ogW41E7lF6w1TWzW1lXWOT2UUi3eKuszdu4DQTcHfJdRZdlhNc2zqjpwulUsAhvgoV+j0GN4U7gHCtxG2w0bF3fdm7g9LdghCwPYVQi1uM9LdMNQqHMP7mgRrSSmT45Fkn4ZHyfOaoBTAe90u6Zt+ndTPFsL5tyNSujvbIgPBfggFrpfv7cLrdz1hRWxJY/Sj/piWhplVHXgO1bMrC85tCOq+xy8o3IR7PsBpGGSAOjkb7t/DsIt/l8h1OLGRrNYInWeA7rv338OoQ6AB7vfGbSfIzXq3A+EKWsEeLZOdhzK9pUQPzuUcgeAl7g4dK0VTYdTbVTXKiiO38/Ssrg5U98AFNDPAl8AfQJ5rTI/Nu2fU6BTsRuANt7uy3d1vk+E0kf4ufrJNqfCCdB9yMSSz6TBEde36S+YSK1XmRZGErxjHxMAXqp3e4jPVuEN13QtXwrL2A6C1XuI7MMuGq/p6djDo0wLVUgmhpGmfQT5GO6cSPVKl5A1fhAoiIvTv51PKyjrXZ1TFS4qcWEbC3RyU+Kg7rYfx8kdzPRYZo+vZFGjYXFnbT1l3+8cSjkb4L2srXtDkLPBoDPrWH/vZu7hlSG/iGqc2DL4c+qc6ylhO6lFwc5BPb4/OBhvf5tou1Kdl0It3Da3IQf0/e9ApROn4S8QQ/8JrCW0qVKljap4BMBr+qv2lRvXGSp8IMCHCOXdxZA3BAGTYfxuir7GzNhj528K2u5zy+p6pzzwWchbyCEVHGDnoM4C3Sl0WD8ODuISnGHh3wYk5pxzSpy2F4CehFkQbY92TD05nTMlmGpUelK/cL1NC6No6vSq8FkAnw3vQjMxtDIELicC+F0mSZ0l78QcZOaFJlCUbgBVa7akVdgyD3WUgX78bWV17upZhDnhLu1Qq86p8iaqOwY6SF0gUuqBIifluQNSsloIdSrhmrpdNw5NOedT2DY0jHIVwCurP6uAPRA6twTviCEpL8yZ+8+tXV4yzXkgwT4O58T9h/BOt2uAHodbJCBLN4FSqMUrfwdrUh6HUbx6RwR1spM2HhDkXzDeT8Ga4rYd8NbUHw1wbZ13APiZL7ZXr34o2XAg3ZDvVXaD8avCJbExyjrxK8A+BnzcPwU7B3UN0FPVbHfgMqEWI4dagrYk1JK0ocA2PNDZJ1Dj9pIajw51cxowNS3cVBDKt7kTwNm2tXULbbTlZ8CbGz/7ZGc3nGfC7AagvL1FUNE3yzeSlH4MePe0JOeXg7oG6CV1ng214IAvBTOrzimYhXZx+IS2A/gQSi63fpS1TOxl25dgzPkeAXChXq8Kbwb4SPXdcl0q2uiyVkbB8wQID1E2b2zJCnwDTQJ9EkrhwM74CB7+QR7oWXVeCLXEatpybW05rBKAnu4vaZAsCAYe7EG7kVb53c9SyncCeEv9Ypn3O56fLQxrD60MhMVp8L1jXH6wqVZPFKz16BRj5ATsHNQ1QM+p8w2wNg210Eom9BuWH20htSOgp2VeWUcqnSpuEex0Z0+wLvXaCthvCPDR8G7mH2k34cnOfh+BXQTfd1H2yc/z1uNVWDNdVPrM9kB1R0+rOqjT8EsW6DscE3Xut+9D2MdBQy0cuIObhFPQvvxQ57F6B8LdjNvH5UAUbhG2UxsZaqkNI6iB1wHmbw/w2fDOtCk82dnQGTuA8VS8HLTrxQNYdugNGkZpJUVJ6Ze6l6BeBDoB9VbmYG3ZUEt13JyBdazsARJKccAmStv1n4RUojrUDz1wxTo9VoRSRbsz4D2g/YwY+Cj1XX2dVtavXzRrEJSngfhqwArWur+iShu5n0v5DUYS6GPA52L0bHw8BrrZLh5OnedCLSnYG1IUHbTdWC18Jk+iwC3CkArjE7RevBOkv8AYwPdYU8qisL17YrEXyiMBfoL6rrrmGy9n14fqDUE1DofYJBhfruIbbOaYPTByxzuj/J1C9haFZ5KnG8nfxlpZoSOjzmmoZe/PQ9qHVwiMdx9xXJxLUQSpc2xPwy1sSMXfhA4H8cJggO56HchxfcezgDrpRtFSv1Q2KnSivmYbrm3Jt5B+WN9BYgNhPB3Abwj4bjO642ql75FR8bFqp2qd8+JBKwGdUefhfcH6fmKlzcE4GzcnoGbVOY5fEa49C3S6fxzUYxXOKXBOqY+wogqtb9sL71ofd1Tfs8Bdwz19aGUQmMdPhg72x9gtn0JtsOCBn9IuUfAkfpCeDwunxh2djzIu9JIA3WxAp+rclSXKO46bE/Ue1s3Hzekhyd0QaLjF142AzsE5p8o5Zs8841TX4CgVPMjPHdV3z3Fs9if4f/YCetyE6CA/u50C33fgexCT1Q04uy46o+QTsC8xuDNAJ6RMslcczG0aJgFpvv2tnwSNy+M2iH0QdY7ID63LhVO8PzKYJB0RqU3JMedsgkqfDu9c34Wy7DXwDvAW6vvQylClPMjXOz/+f6WKr1LesRl57CzgI7DHUDcLDa8wQCd+jjgzUeBSqEWIm2smQbdyI8AeIpCDv6PsFrobdL+kFMSgjQDtM8+g5knRQtnt4V3yi7HwnpW9ogut3A3ME87w7xI+Aer3pQh+ryTDwgTsOahTlR4BPQm3RDAPQi0KmJcmQakPVpFTv3HZcTiSGwNzyHw9aVvOtII8l+UyOl+5VN4K4ruFTi6DdyPom57svCOQp4D4u7/wwsWgM8dODLNEyj0H9RLQvYqOgJ5krsRx89wkaARzgFPpfNzcKfLk/rJXCMDs6sYKnXTMxc414RWVMaGurA1WhMPBXerzDeB9xffx3Dq+F5iHQnkGjN9ZvVP1nTs2AuTZddRzUC8A3cfQY3Ueh1qEuLk4CUpuErHKDusyN4SoLrO7wTYu5LJ9TqWypMo5UZ09y7iBtVhF+67wS6n9H/DuqptfNOtuYB4F5YkgvluuevUj/A7U3LFetOEVm5ZxQM+p82BMYahFDfP9JiHB3PWT+Di6Df9OfjEcPvjP5BcFY9lQS0ZpT10YbSBkmsFdKH87eE9U6OSBoNqGN4LyQCCfAuDZSl56HZvCjqcPmQYc3BnFnoK7AHStOvdNZZgDYMMkucf66d/lrBhZBGuB7vxzltxv2Vp83ammPH961XoZvpPhPWo/K3xV18303/byZcluBOexWTg3k9mS1Y6T5kMzTUW4G5OFeg3QY3VeCrXEMAeQnQRNYJ4o9hjsudj78TcQXYP0BpWpxz0ExRkbahkVTumwYSp0Mrg3H31jUPmo8NVSV9s/+2Tn0LjyAAgOgfIbpzIOM22Yxa0vEhWzYGegrgZ6DHPApysGE5YZmAeToBmYO59JeiIL9jDUQuu7v8F8hrCdC6GUlv7lTKvEW9Zqab7GBoFuxOJUtw2ZTAB37PdZBe07qeWbTdBSu0sqY/LqNu3vdU6BI/zeEqjH4ZcC0IPH8qlPqs5J3JyD+bZLRgXz429ygwBEUJdWYnT14jIq3RPQM6qdHpPj2DJqvRQXJ9/fpc+EKOuftqqgejyKSjcCd2z3WjRrxFgGncSnwrjl6dqlLLtK+6DNH08UOBioF4AeZLto1HkUagkmQU3opxfmfB13CPiVGLNwp2Pkysi2eLvrk1rpSVvWyWyrgpWy8ii1/E1Vd86C0MrwCb+bgHncBO09lDaA9rGQG0D2CU5AUIUy1LnVELFCr861cXM/FuKjBeZAfhJUUv8ZgGuAHh/aJOIVfRZfsVeIs59to188PBK2bwHuyu+S+q1bj/xG4YwhcB4M5tunHgLyPguAZ1W7oNQDoLtyGkPngH4FzF1TovalSVC/29QXUAR4VijTEEscMjHhecSmGu7Oq35xdVrz9XYR8N4C3AP9jgmtDAJYN5wHgHkqjGeEazIXa2lfAtAzqxluPgo/82OoJwtjHdudOnd+T4e5q55AO4U5IIdatjITjpOM27elh4cDMiln65j0OyzmkBOHp4UHG7oZDdors0uuAHdsw9/ZGQ7ketU8DMw3mcBMrGZcEfSzKYcFsCfhl1iFg0CObudi5wTEm8tI9Y6CueLBIb9LooKP+qHjxFFZAnpQL7JSiIWr4+tmfwJcY9XX3kXqvbbuHcAd+616IGhszvnFgB6ejnijKwjglXruYR/3Mf5Z74w8vLPVywC9Qp3HGSycOvf9T4T5tgupT6q40/CJcOPxBzNS7GTbcUzocSPHmwuxIKpDOtVcD6NeIdd/7U3s743AXeW7UG/MA0F3eelE777MhPGMNV+WTFluX4K4twx3FiTJuuN6oLPqPJPVkuRy98IcG3w5mAeToNQnhFBL3BeXThm1p9ty2xOoR3V9m4owCzDw12nJGvuZqeDvHuPu9RuGViZkZdwiLXHIzarfxXDTjikGfkmZa9INgWgBLAboEbgTdZ7LamGUubEDYG6VMAcQ56/ns1W48Yd1cmo8N/kZOjm2SdfWHcMszqY/eNRQ/xaKu8I357P6DUFjHza4GNAD4XyHh4DELAVhAaywcQrvYDvzOH8AdC7kEqvzOHYewdy1z8Gc9jcS5gCnuIW4eQz3qL+tvqNtBdDJLvrDH33m1HrcsGqSe6CNEW1z20xV/bX+B467Lv0wZ8NSE6+F8zmviKs9O3RXXlU6WnycKNg5qJfyx5kYeqLOuVCLchI0UdACzMP+SPsCzOXJzegmATl0EoJaAXTS1h/HqLCYiugHy2znOsGJIZbYevptaHsraFf6r42d82utzIDZdwH0Fcp7EPjFtcUBdhGsoO+MSg/i35E6L4VaEgiTsbIwp/0JT4Bm1zTXwNy4MgbmWTV+7Oo20Gg/ENUTwitJGVPu6yCqR+ofFZlyjUn6YeYl0Oi76eb0juAW/LblkQ/NXulr3g3od81eyal0aQwMLINmmeVqRZVeUOdc7Ju2rQmzbO0QQnQQzDfXhoX5VrbViddL59V4CGJ2xcNMeEUDdXrMqanj45ofeSNP5UG+zgB2Uz8zbwqKusPWWglsQOy5C9BDHnK66ven0jTjSxbNstnyZMISCEIegZ845KJV55Uwj8dXszYLB/OtXyQwT0Avqm+FOqddVQA9rq8qJ/Xc8ecsiYvf9PQ+O7Wxuc+LwX343SrzoRVqg7M1LlfQN/o1McRqUxAL2SlA+B0lKj1W6II6HwXz5idAgQS2bChlFMzpLnHhFgboAI4YOpj6ONrE5cf3w9Sjg3EfFaf9rElQbf9q6/D1HRQ9x9C6ZWyVTpvsakCfBOXh62Mo3rsZdsDDuwR1FdCjycytHa6BOXjlXAVzOkR3PPxnu382x37G8MbRSI6LK1V64PAYSFXcnBpzml02CUpt0BhOS3Ns6atazZcbjH35MmdXhzkGAfqs9MKWfprTDqtSDhmg58It3MQk4OPms2HO+0QdzIVJUI0658It1UCP2vhDzYVXMqEVVmnXnmYtan3yJXNFGKap3wngjn3XP9k5EmjfJZMltpF+FQq9uBwttVJ2Cu1TAHpWnStDLVNhTvs8C+YoqPNKoG9lKdTdvh113B9ILQN3aqqQyslqfVxa9AVjOAHcsY2f7Bzh7w6Avstkp3YcDLSz6YaAPuUwmdDMqPNemPuxt8E89D8Z5qTLuB+AXHO1QPdldVD3fvwH8MYc67e2zvF37X9D29HrtgOlyc4bZrRcPll6lk9qmrh5aWITDBioSdkp1A8DdFadx3FzDuZkTAGI6Y2AjoODOWO5TJaRMN+OIZAC/tj3utAK2Y6wzB2nrdyE5YjrpcekKmOlJYQyywZfVteFYiobarUbqdevyO8Sg/5OKjw2zbg4sMXtSpkpQDndMPqsUudSzFyaAI2hK1lJNQ+G+dalIyYfatmORdjXsQ1B29z2pMyXC7+yBLBvx1c4fNyxvekloLF7hGPmQPvwz2/vzlopd3wDwI4G9BWvfCu9ozMDbbZObiITqEo3dD6mwnxEJksDzAH4lRM1oZacOt+OcVqX2+6Oky8DKQ/qKMFO2viPitN4Zkqi1qaEfgb4bGLbIHDHVs4jZ50PPLJ3gPSd3sUpWW6MHORLYNdkpgDl7BTioxfmRx84F+b0MHHKuzHUcmxj9pvuJwSgI/Tly5HWicd/1Ke/pMBbBtZvHT8fNPa+hxNr+2rzPWY98qSDQT67wz43uuH0WClGLrzNJzBBjatTDQHlw0ACzGl/AszZ2PcZMI+PFecnB3NEfbWoc1Lfl0EuF+vs9fyfzHmbHuOkCm9Xq/OJl2B/aLe13zH96BT5HWE/AtJ3jYnHlhsnm2JI6uegrgB6lTrPwVyoG4y5kMlStJY2GT8amAOoV+dACnTXL1AGdqTigzq0njPhV0ey2yXB8CaXC2djowg945jT19j0w1G+eiE9GtB3VuOlEEoO6gqgtz8IpIN5TSZLUZUL7avj5QBUMAdfZxsDr863Yxke53LGilDO1HFWTENkTist7KqfPp5kcx9k7HcxezmAMGuFdTbxAN0B0u+ixAF5rNLFJIVQABnqEtBzk5mAIndcDpUEuxKBNqyPOpj3hFhqYS7VwdEnkPqtBnrkT6yDtI/gUJbgHvkQi9/p+pFs4C6cmYcuZ63cbbLwDpOfM/1prVeJx3UkqMdAL6hzMdRSgnnl5KcqV/ximAPlUEs4XrcD0fboWA8LqyS/dMLPYkaK5pS/hyhPbeLlekUeuj5r5ayMjbso6XdRE7Vx8RLYOdUNpEAvqPMWmGfr1sTLubqSnQBzAEncPDhGOXXObXfHBQhucGE52cdSWIU7hcjhy0GimHb4JpdRjQ3N0Gn01Zy10tadc3QjJT7KR2Tm5NREW8oXB+rUeA3QS+pcEzdn4+C6TJYZ8XLOhsEcCEMtAaD5tyMl6Ye+/r6pAPSwDt2pcP+Sun4Dd0CYTYrT/g455hqbmkLZ6Xtc1soZCvVGkD4bzLUmjS8L+FwIRSrjgM6p80zcPDAJ5q7r0uSnrxdClrXOeHk47g6Y021C3BxAXp27+mJZ+v21Qj1p4zekdWI/bPG9L6VxNmg/Z05+tivym6nxKYA+KwyjCBdw+8fCXQN1DdClUIs2zEL9ayY/a0IsnLXGy4llYY697wLMgUyoBaGv+vTD9LuqzSuP2yRtg43MttjeRJWzNunyvmLy820U+TBQ3zFGXhsPd0XkmGShrsgcSbblQi0lOGfqH/5RFWI56oAPseSsBHM2WybjPwNzQA61AODrZ4DOl/M369a88rgt60OyEZdT7c3gJpfwkF8kDT64ftsU+WAYDoH0TECP9l2Th8v1zbTPQl2rxEfAvCVergixdD31yZkA8ySTRKHMAUCcBCV9uWMV1Act26sXgB7WKUM9qE/9UlPCPbYhcfKbgJnandZ30YxluiK/nZK+gyIvjaEm9TADdTXQz4K5G9/MEItvg3yIJRhPBcwB8qsASMInVIXHoRYw9cGV7ZsFoLN13Fh9hXQfqV0ZJz9zkvSSOH5nn/UToLZx0azR8eh3hHQvjGt9i8oyc/HmgJ5T5/HnXphL/RbqNYVYcjcOIcSy1RkIc0TbNerclSEc01aOsJypE9RzYw4OQiXYfYGwnYyh1t5+knTg+NsmQNNGz+lZHHeE9B3nBWpUuFRfiImzQK9V50qYi2PPhVik/qEMscR1oxBL2AdEmHtrgTkOv0AaOimpc98GXPm+mQuPMCo9qevGT60AdtFPUJgp4+xEJV5lJ91Y+iZB843vkbUy0t8dQictVqPCaf1KoKvUuRbmjDWFWLTqPW4XqXLWMvHybCZLLcyjv9XqHGEboAz0rU7kg9SL6wb1/QaFMGD8ZH2W7E0vzRob9mujkmNvk7Uy1I+zK3PKRz/4w5UzQBfVeQvMZ4RYFKqctYYQS9gep8IcaAe6OyZbnWgfkNal9X3VEth9Q/k8/U4PDWlsWkiogWvxWL6fIgfe+0URrQ/+0HJNyCJW5yWYU6uFeW4cEyY+m0IswbYUQMNgDlJG1XnsA3VA3+pFvoIdSPeHmhwjrwd8rp8Rpr053C4W38m43P6co8iBcaCeCekZx6J20lPzkgigHFoZDfNSHDxnPROfbqwMXA9fkEMsEcyzIRauv+B1dJUwB/zNAkCTOnfjS9qDq0d2m/vFwbTh2oo+gsLCtdIz2V+w2wGa2kCG1Oxn31orwL3DHXeIl/ee8C0viZC2C6GWJpjfSZUz7XLg57NWypkswbaoL8D9CnCduDpMH0jrNQGd1kvqkio5qDNtOR9Bcw2jW669ifDvshM40nxz2tuFID8DfHfLK7/aaiY5uaVnYz8KcMbbijCX2ipgfowdU9IRWx7fD8uYdg0wT7cTvxHMATlcUgP0wA+tm9SPdo87ToVQTFCUufS6YuLf5ZrOWPevCaH9uNDKXXPLZ/lrMa3iKMXCO9/647dpYd4RVhmiyjmrmfgM2iENseyglSYnuT6bYA6AVedMfyLQARbq2fdwJje/qKoG7IKvpFh5mX2nSVBqw8M+Sn9yaOVdYtF3ALTWWiaOtFAvpRVy21phPkKVZ0MnGKbK2SwWbbzcA5702QJzkHFVqHOAAbpUT1LptH7U5mibbpv9gNBI4I28KVwaf+/oe86LJd4F1OtartNiizBjJ1kJ1nE9CegzYC61lWDOmGaNcLFepyovbcvGy4N6HTAHiuocGAN06i/wGbfxlcGaOqsl5ztxqvDRYLee/JRswJjpfusnO2cBdaTfWWCutdI4cqCPj0dNmqH0+ra4bg3Ma8MqN4yV50IsoX+kMA+21cMcEEItzGc23IKoTg7oUV3n01djz6XosxLsgQvt6VF7qb9r+GUCKks3q/nph98R1L0W74cG7LVA73mCk+unJsTC2KmxcgfIWlVO23L+UA/ztMxt5D9nM1MYoANtUE/64NoLfpLiEZBnG3e0fXOr/ZVxn1e9AXNAfWUMXatk6X5LUC8BfTDMsyGWks1U5btlVTnjlwUt8a+Nlyd952AO6EItzGct0AFBpdP6TBvah68u3sj5zRrF/Ht7+rPWRq1pfoD8DOCNBPU7THK2TG6WoC4BfRTM6TClEEvtxKfzN0KVq/cTY0MsyXYFzKP9Ky5PyynvHNDjupJKj9tE7eK+gmbZORu56IyJz7vfAOY90p9uGhtaGa2oT4C1bezDNKbj7Z1SR3I9dzwloHOwi31qJ0E1ZS31pLoXqPLSNhna42DOlwOJOgfKQBfqAgWo03a+AVMHDXCX/Cv6qrW3nORsMcV+6kIrs2LTg0HdCuVZfalgr4G6BHStOi+tWqgNsUjwPjtWPlGVj4Q5kI+bh+WuIBp/tK0pb7wE9bg94yMoEs59FeC5vnJ2c9U91Drw9Zw6gTgQrGdCepRxY87CvQT1HNBrYT46xCLtT/YXB6qWr2XHNkqVF+LliSlgnpQxN15WnQNqoAPtUAcqwM74Sooz16ga8ppxaOyON4BJCDO28Q1B3t5NUY/OmW+YDKT7qIK6BPQZMC/5y1lJldf6o6YOwzSo8uLNCGBVeWRqmDN9ikvSxl1JYRRJpdM2TDugAuyxr4xPznKQBzpALzoc6+5Oxh3LU9daGQ7qq5erzfWvgLwK6hJoZsC8RZWXbNakZ1CvXpWPDrEkPqOcfhbmQL06z2yvyhmXYuLMD/RquBf6YKtWsGE49G9qNcdkeB75UFhfDeoe48aegbs7bizQJXXOhVpaYC7V1QC7N9Qy4AGhsJ5OlYt+RsI8Gg+vvJXqHMw+5EIoNVDnfNOiWrhLfSj7K1kN4IB7g792XySrCq1MCX1MXdNl8gNEpvJR/NKStFAAXaPOlVkaqjJiVbnlJz8g1K3KVTctdMOcLRfUOSAAHZChzoVPSlCPfQt+guJWuEv9JR1U+Cq5esP5tSqzwPPt4tLAfEBrTRqHBvC5JWmRAXpOnZdgHvdfu0BWPI5Rk56jraTKKyZh83HxPpgDeXUu1nP9ATLQuTKkUKt6CKgB7t5dpeb5I7NFMOG49L9YwtnQF0LcBNStFo8/B3YF0NXqvATzmhBLq90hvEKslIEiqnJFiKVcloc5W0e4UVcDnZZJ5agAe+yv4DepNhLyiQNlvXcDfgVSlXnkb6Sqz/oZVZXRQfZVgnoG6Fl13gtzyZ/wd9Wk5w3CK2Eb6FV5bqy5mLsG5kA+1OLGB9QDHcLYlKGTKrBzfgv+2aoKFHTDHqhT+VrT7OcJSJqzjK2z0bC+U6yLG4sGDCWoF4CugnnaUK4zSpVfGV7RTnoKplHlaZ/g4+VRWeJfGJ8M6Eqgu/59xcz4S3XAx5eveLLzNNjX2k2QNOCdnd8Y1rUWj70I2P3YSUBvhTmXmpirL5VpVHmtf6l8wCP7AA9NUU1rJj5z8fJKmAO6UEtSz40JEIHOtnHj8JWZ8rhOrp7vsxHuUn8VfedMA3vgIuAPtnhfyyCfEQKZBesz0hVr1CvdzyzYBKAL6rwJ5rNUeWnSs8V3R3ilu++CqSc/ATYEowm1uHqAHujZNnQ8QQNlvVxd37d87Q2DvGIcGtMCn9rZ8K8d43PqxOJoYN8hr7wyP9ybBup2VavzbmV+diaJ0Kf27UEtvsV+OlR51ldc5soR1ymHWrJ13fiALNABxZyBb5SpF9fVtvHj4a/bpu/9BNCzbm+efzEgtDIQrncAdYvF4y6BPXMRZtW5BualfjWq/IzwCjsGTAuvdJsyXr71z/16iOvsm3vUOVAUCOpXtrWAunOi87K1WU7WL2eYDuTvpKxH/8KofegHUD34A6AQq2bUuQbmNSGWUaq8JcTR0HdveKVLlQPqeLk8ViQQEdU5UAd0N16g8MuEVK8Ftfbr6gQ8kIc80AF6oG6C8u7Q3/dlA/m7xKyvyC/veegHKOaJF9X5DJjnxtqyymE4mHMAPajvHp9TYQ4UgQ60qXTOj+grqMA5KbQpta/14ZrMUPOss8r6M8CvGMOYtVZ+jw8DcePsePBHfoJSB/Mq61HlNeGVUt89VhNekY6XRpUX+h0Jc6AO6MV2QCrSRoIdGAPnHD4GQx4YDPrE+TzXOauLkb8bsGvH25vhkEsndJYDuqTOFTAfpspH2sw4eWM/TZOrmRAL65OBOYC0DjAc6GJbX6hT67FPle+gouRU2b7kp8WXa3Yl6CdZCvK7h0NmxtdLvrWg73ySkwXTCJiL4yX1WsMrJ8XJi9bjM6fKq3+5gIG0Tp27/oF6oNO2YntfqFfrnG9VH0llyXGFj5KvVn+uqSJKcTfYj3uycySw75q90pJ6WFLp4s9+JcxrjKryQcBrKu/op0ZRy69h0z1u3xViEXyL9cCPIz8Gcj72Qh3g58oa4a7qL6ic66DCzyx/sYvKkPQM8NMxtKUfjoL2XYFdY+oMlfqnOFUwH6XKG21UnLwp5FGIkzdZNpOoMsQC6GEu1N3q78W5w1Oag0EKXF0MvA3uXH9V/QYNpA4q/czyp7DZS+nmQX5zYM9egrcqRxtQXUzZh364tiNgHvQjqHJNeKXFzkpx7JrARZsqB7pgDjBKraDOfbUOlc75y/qMrQPuXL/V/fsGuU4qfZX8tfo8yfb0w3uGRa5+4XL1y5OdFTNUKtX5O8K0xwYqbVV4JbYaVc72WRMLz6hz8G22dns1jUoHVPM7fZObwrU6APBV4/ANpE4q/Wh89vodYH2P6A+C9tXArrF4rFmwa4DeCvMeVT7CmjJSxtykhj3Wr+6vMPHJ3HiGwNy1Ad/Ojc1X1UIdqFoZMhlSVey7H/BDxuEbSR00+NL4HeW/YPoY+TtAe228KXWk5WVfzeYsm6FSAXNt25LVhlda7LSnRtGs3tVrjGtsAMyBzKRYAeibD1K9tC+tawaBh6qqz6Dy70DBa/yXLNc/8cmD/I7QboV0r28l5Om+yvFpaVJTCfOWFD9t25wV2jZNeHJ+epW2Zh+1N6jIlyodsQbmwDSgu/H6JtpD2qjauT6r+/YNficKvrf/yIalHw6D9kxgt1g8HgXY85ON0qSmUl2XQizacbTaWUq7t432Sc2gDeouUOV4arNUsm1oW1+51H/UtBXszioAP25is2+CdehYgOsBH1nz6odDwH03aGuMjjkD9WLIhY0XD3gcX6vKNeGVUTY5BbLHaiY9VTcEIdTTCnMgo86pD9+oMD50gN1ZR1hGGkPTWO6m3oHLJkTVIO8G9yxoj/ol0AIat0+tQG+F+dWqPGcnQfvsCU/RlCEWoCdDRQl06ivjL/XPuBkBd+A+gL8S7t6B1FmnXwggvxW0z8po6bm7K1S6CNRRMC/5bLGSn5nQnvGwj/ed+9WC8MLSqPIRMHd9A0WgAw1Qz/jl+xJc3gjw3wLugC4OXujnCdwkTHLXFEQ6Li3UZ8E8O87GGLva/0Ro9/qWoN8SJx9pLTAHVLH6aqg7v4ETXbOwX8H1BYD/1nBPnOaLn80Q7wH3XaFdMi3UMyGXLpg3qnK5z0Frr0jGKtVBvxZq+ixY8V2braocyMIc6M9Oob6y/nJ9BM70zcMxCF2cHH8fDveGa+I0uBOryCO/EbhnxNtrc8ndPpWA3gvzqjF1Lqrl/TTAcFAK4qjxzLYRMN/8KLNT1PHu8FqrX7JXclzn5hiP0E2Nv071PvyJ1RvCXQb5HcB9ZlYL15cG7iWgC+pcPQlZUuVX2A3BWm1nH8cemANNk5jOd+Cm+VkCqYM2d1MmWDuU+9mqnRtD9TiIhSC/Ct53TUNUphoC0AFdA/NawLSEV2pAfIcbxwlWVsbpMatS5UAR5sC8zJS4n8Bd10NYuc7qXHWr94FPq14Bdm4c2rE8myH6HcGdMy3Uc0BvhXmNKq8Nr1zx5qCLrGrCUzHhKLdtgzlQCXSgC+pxn6z7GZAfAPjZcL8L2Lmx+G6I27oHgq6YGGWHMS7m3pRjrcgfl+OlSpgn/jKAvvJpy8HWooxPM60qF+p6U6RWVgMdGJKVIo0j6epiwA+D+5sp9sANcVsG+UXwPmtFRKkf3XK1BaD3wLwU0rgi5MHtzw3gn7Wbgd+buzyUQAeun7gMXMxQ8Z1ZNE2w/QaKHZBAfgG877aUrWoRLGe58EQFzNM6hRCL1A+tp0lDrBn37LZnWvGBJyjT/zoyECoefGpS6ZxNBDwwGPIdcB+yxkyDYu9aR6bxuz1AfjK87wbunOmWqs2ocyXMqx+n71HlZ8P2zP4a+9Jlj/C+m0IszpTq/OhrUCZKbKVL8i6hmka4D1HslWq9e3Ew5XF5NgG8Ad5jl7Qd5KsSgmqg18Cc6SMbYhmVK07tqgnPd1Huvabdz8ZlCYZnokg2EfTd+9AwP9AN9tkhGECt1qc+ENS/Zstk1d6Yh1pe2bAC5rMgKoRX/rBK48Irtao80yaxSnUu2ZRJypINTEUEOuHeCfYZUG/qg1pGredBfia8Z0O7ZQyFLye/sqEQalHAvGris/JFyU2rIf5xIxhjmqeBndFLb+B9XvM299PVfNWEZiPcK8F+e6gDAdiFNwTVAfyt4Z2z0js3d1O/tf5o0BdSmBFe8b6VYxsRFvmGYRXVxGftsZsEdck0sAcmx+Y74D76oaozoX7Jk51NAB8N75qXR7fCTwH0aqUbX8w9qrzVfi8x6hmWOXZTYO6MO90vep6rBPzhuebqbJVKsJ8B9ckqfQN5BcCr4T0C3DWwbvGjBXzhSxFDLdo4eGsWixRemancv6md+sKKmlBLzkqXx3cBfXO2ytHwMqhPDr2oH9E/DeCjoN3apwZ8CqCrYN6Vq137KP57xLmLF9oVvyC4Cc+C1S0HMPmXUeslNfkGMCTbpgK8cZ+XQ71hkS/JdzFrpQrgLfC+Atw5q4F6Bo7NMM+p9zeBMWvfMYRTAHA1zH3Dmxyrlkvzymyb6gnNihBMA9RnqvTYtwjyqQC/G7wlc+PMAT1zd1XDPDeEliyTFvtOi2fdBYStNirkcoVNCvN0T2gCVWAfAfWZKj0GegLyaQAfBG87aLLUVC0VqwR6K8xbVbmUK15Qivq10P+YDO21rsf3uWvx3b+PHAYqID8/U8Xq/Dqfo1V6JdA9yO8G8FHA1vpXgb0E9BqYV1hX++8w4XlneCludkPfF3rl0hazv4eOjJxZmSrVKv0ioNe9fFkL15vCW9t3Eeo5OGrj2D2q/A97O7vk5c+jrfUm0nMDaIT7jElNlUqvDLuMArru5cuTAH4luHPmxpUFek6dMzAfGuuWwivvajOV3o3U/LeAeYuVGFP9pHH0uWIpYKBfWY9U6aOAXnhEfzzAh8J78sNAaqC3wrxClatuBC1rmM+Ig4/w9073popj+LuFec4k0GvPow6wiyCeodJHAZ25xjMvX1YA9yyAj5go5Xwo4V4EegXM0zqzFs266UTlu6ZPDrTex7HPNOk1Y8AJ429c0rVmSYNxIB4H9BZ1noL8DgA/Kz0x7qcA9izQlTAvKuu7AvhmFlww76Teic0Geg7CV/vvXSTqGERJKJG/Fe9KBfpUuhrog9X5MykomRKy1QC/Q265Js0Q275VwTyuVgqxUJPCKzVx8u8QRwd0N7jOm+Bpj+cT06re2WA+04Yp/ZoHqSqh3qOuiz5GhVt2zj7jDaLNAPgd4M2ZAuhVMK99IrNHlSv7OuVBo0r/syGaXBBvEOb5TvDWWvOLlWtCMQqoV6n0yUBXrLUyRoWrAT4k3n1SGlQB6D0wr1Ll39G030UP3M9U1985JNabuz7guDS9aUer1hUv8+gFsqp9hzovvyGoAN7pAB/5AETr5EkG6L1hFpVpwitn23eF1u/NznjASNNH5flUDXYN1CtUeg/QZ6hzGeSjVHgtwM98cq0W7AKc1TCvUeUjFF6rj9HqMueLKyvc/77DROfpduUToRrrTEGsAnsN1HuAPlGd6xbNGqHCawB+l5NMs1hRLcxjm6Witb8ARvd/ljLvnOjUxMfFC+sdf3zc5Zrqtcb1ZtQLVpWu+R6gT1TnMcxTkPdC/B0BHlvpy62BeQGw2UlHqoy/eQx9+ETn7y30c0qIZKCvnq+n8pe0KvtjANBboNyn7I99+v8BSPSrGUI3lOcAAAAASUVORK5CYII=\" 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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
        "     <g id=\"line2d_1\">\n",
        "      <defs>\n",
-       "       <path id=\"m4bed6e31e2\" d=\"M 0 0 \n",
+       "       <path id=\"m2aaf06a052\" d=\"M 0 0 \n",
        "L 0 3.5 \n",
        "\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m4bed6e31e2\" x=\"33.547375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m2aaf06a052\" x=\"33.547375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -3239,7 +3242,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m4bed6e31e2\" x=\"85.522375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m2aaf06a052\" x=\"85.522375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -3270,7 +3273,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m4bed6e31e2\" x=\"137.497375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m2aaf06a052\" x=\"137.497375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -3311,7 +3314,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m4bed6e31e2\" x=\"189.472375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m2aaf06a052\" x=\"189.472375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -3360,7 +3363,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m4bed6e31e2\" x=\"241.447375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m2aaf06a052\" x=\"241.447375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -3396,7 +3399,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m4bed6e31e2\" x=\"293.422375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m2aaf06a052\" x=\"293.422375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -3440,12 +3443,12 @@
        "    <g id=\"ytick_1\">\n",
        "     <g id=\"line2d_7\">\n",
        "      <defs>\n",
-       "       <path id=\"m91ab8c1677\" d=\"M 0 0 \n",
+       "       <path id=\"m8a5fafe075\" d=\"M 0 0 \n",
        "L -3.5 0 \n",
        "\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m91ab8c1677\" x=\"33.2875\" y=\"10.999219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m8a5fafe075\" x=\"33.2875\" y=\"10.999219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -3458,7 +3461,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m91ab8c1677\" x=\"33.2875\" y=\"62.974219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m8a5fafe075\" x=\"33.2875\" y=\"62.974219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -3473,7 +3476,7 @@
        "    <g id=\"ytick_3\">\n",
        "     <g id=\"line2d_9\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m91ab8c1677\" x=\"33.2875\" y=\"114.949219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m8a5fafe075\" x=\"33.2875\" y=\"114.949219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_9\">\n",
@@ -3488,7 +3491,7 @@
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        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m91ab8c1677\" x=\"33.2875\" y=\"166.924219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m8a5fafe075\" x=\"33.2875\" y=\"166.924219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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@@ -3503,7 +3506,7 @@
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        "      <g>\n",
-       "       <use xlink:href=\"#m91ab8c1677\" x=\"33.2875\" y=\"218.899219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m8a5fafe075\" x=\"33.2875\" y=\"218.899219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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@@ -3518,7 +3521,7 @@
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        "      <g>\n",
-       "       <use xlink:href=\"#m91ab8c1677\" x=\"33.2875\" y=\"270.874219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m8a5fafe075\" x=\"33.2875\" y=\"270.874219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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@@ -3562,23 +3565,23 @@
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        "   <image xlink:href=\"data:image/png;base64,\n",
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        "   <g id=\"matplotlib.axis_3\"/>\n",
        "   <g id=\"matplotlib.axis_4\">\n",
        "    <g id=\"ytick_7\">\n",
        "     <g id=\"line2d_13\">\n",
        "      <defs>\n",
-       "       <path id=\"m8f8c3bb833\" d=\"M 0 0 \n",
+       "       <path id=\"mf25850c8d6\" d=\"M 0 0 \n",
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        "      <g>\n",
-       "       <use xlink:href=\"#m8f8c3bb833\" x=\"330.5611\" y=\"246.87621\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mf25850c8d6\" x=\"330.5611\" y=\"246.876856\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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@@ -3586,12 +3589,12 @@
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        "      <g>\n",
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@@ -3599,12 +3602,12 @@
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        "      <g>\n",
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-       "      <g transform=\"translate(337.5611 170.452725) scale(0.1 -0.1)\">\n",
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@@ -3613,12 +3616,12 @@
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        "      <g>\n",
-       "       <use xlink:href=\"#m8f8c3bb833\" x=\"330.5611\" y=\"126.542155\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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@@ -3627,12 +3630,12 @@
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        "      <g>\n",
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        "     <g id=\"text_17\">\n",
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@@ -3641,12 +3644,12 @@
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        "      <g>\n",
-       "       <use xlink:href=\"#m8f8c3bb833\" x=\"330.5611\" y=\"46.319452\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mf25850c8d6\" x=\"330.5611\" y=\"46.32016\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_18\">\n",
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@@ -3668,7 +3671,7 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
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@@ -3692,7 +3695,7 @@
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        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2025-02-04T16:11:02.553874</dc:date>\n",
+       "    <dc:date>2025-02-06T12:27:06.007722</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -3723,20 +3726,20 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#pf365f295ff)\">\n",
+       "   <g clip-path=\"url(#p124d80356b)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
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\" 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+       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id=\"image737f6a0ed4\" transform=\"scale(1 -1) translate(0 -266.4)\" x=\"33.2875\" y=\"-10.451344\" width=\"266.4\" height=\"266.4\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
        "     <g id=\"line2d_1\">\n",
        "      <defs>\n",
-       "       <path id=\"m8577516c22\" d=\"M 0 0 \n",
+       "       <path id=\"m0da1958251\" d=\"M 0 0 \n",
        "L 0 3.5 \n",
        "\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8577516c22\" x=\"33.547375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m0da1958251\" x=\"33.547375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -3772,7 +3775,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8577516c22\" x=\"85.522375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m0da1958251\" x=\"85.522375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -3803,7 +3806,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8577516c22\" x=\"137.497375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m0da1958251\" x=\"137.497375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -3844,7 +3847,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8577516c22\" x=\"189.472375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m0da1958251\" x=\"189.472375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -3893,7 +3896,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8577516c22\" x=\"241.447375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m0da1958251\" x=\"241.447375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -3929,7 +3932,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8577516c22\" x=\"293.422375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m0da1958251\" x=\"293.422375\" y=\"276.851344\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -3973,12 +3976,12 @@
        "    <g id=\"ytick_1\">\n",
        "     <g id=\"line2d_7\">\n",
        "      <defs>\n",
-       "       <path id=\"m9e12389cf5\" d=\"M 0 0 \n",
+       "       <path id=\"m1be7a1ee9d\" d=\"M 0 0 \n",
        "L -3.5 0 \n",
        "\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m9e12389cf5\" x=\"33.2875\" y=\"10.999219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m1be7a1ee9d\" x=\"33.2875\" y=\"10.999219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -3991,7 +3994,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m9e12389cf5\" x=\"33.2875\" y=\"62.974219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m1be7a1ee9d\" x=\"33.2875\" y=\"62.974219\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -4006,7 +4009,7 @@
        "    <g id=\"ytick_3\">\n",
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      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:190: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
       "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:191: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
       "  gammat_radial = _GT/_N\n"
      ]
     }
    ],
    "source": [
-    "kappa_radial, gammat_radial = mod.getRadial(radius_map,r_bins.value,\n",
-    "                                        angle_map,phi_bins,kappa_map,et_map)"
+    "kappa_radial, gammat_radial = mod.getRadial(radius_map,angle_map,\n",
+    "                                            r_bins.value,phi_bins,\n",
+    "                                            kappa_map,et_map)"
    ]
   },
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        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
        "     <g id=\"line2d_1\">\n",
        "      <defs>\n",
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        "      </defs>\n",
        "      <g>\n",
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        "     <g id=\"text_1\">\n",
@@ -4400,7 +4404,7 @@
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        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
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        "     <g id=\"text_2\">\n",
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        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
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        "     <g id=\"text_3\">\n",
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        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
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        "     <g id=\"text_4\">\n",
@@ -4484,7 +4488,7 @@
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        "      <g>\n",
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        "      <defs>\n",
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        "      <g>\n",
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        "      <g>\n",
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        "    <g id=\"ytick_5\">\n",
        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
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+       "       <use xlink:href=\"#m6cc1d62c92\" x=\"26.925\" y=\"189.0432\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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        "     <g id=\"text_10\">\n",
@@ -4599,7 +4603,7 @@
        "    <g id=\"ytick_6\">\n",
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        "      <g>\n",
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        "     <g id=\"text_11\">\n",
@@ -4634,7 +4638,7 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
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@@ -4658,7 +4662,7 @@
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        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2025-02-04T16:11:06.718096</dc:date>\n",
+       "    <dc:date>2025-02-06T12:27:10.276872</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -4689,20 +4693,20 @@
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        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p5a9925200c)\">\n",
+       "   <g clip-path=\"url(#p77fe28d60f)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
        "     <g id=\"line2d_1\">\n",
        "      <defs>\n",
-       "       <path id=\"mf2f2378a85\" d=\"M 0 0 \n",
+       "       <path id=\"mf649e57bcf\" d=\"M 0 0 \n",
        "L 0 3.5 \n",
        "\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mf2f2378a85\" x=\"31.3602\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mf649e57bcf\" x=\"31.3602\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -4738,7 +4742,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mf2f2378a85\" x=\"75.7122\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mf649e57bcf\" x=\"75.7122\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -4778,7 +4782,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mf2f2378a85\" x=\"120.0642\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mf649e57bcf\" x=\"120.0642\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -4808,7 +4812,7 @@
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mf2f2378a85\" x=\"164.4162\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mf649e57bcf\" x=\"164.4162\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -4822,7 +4826,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mf2f2378a85\" x=\"208.7682\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mf649e57bcf\" x=\"208.7682\" y=\"273.312\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -4864,12 +4868,12 @@
        "    <g id=\"ytick_1\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <defs>\n",
-       "       <path id=\"m4ba80c9bc3\" d=\"M 0 0 \n",
+       "       <path id=\"md1bf286349\" d=\"M 0 0 \n",
        "L -3.5 0 \n",
        "\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m4ba80c9bc3\" x=\"26.925\" y=\"11.6352\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#md1bf286349\" x=\"26.925\" y=\"11.6352\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -4882,7 +4886,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_7\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m4ba80c9bc3\" x=\"26.925\" y=\"55.9872\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#md1bf286349\" x=\"26.925\" y=\"55.9872\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -4895,7 +4899,7 @@
        "    <g id=\"ytick_3\">\n",
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@@ -5009,7 +5013,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "kappa_1D_radial = kappa_radial.mean(axis=-1)\n",
+    "kappa_1D_radial  = kappa_radial.mean(axis=-1)\n",
     "gammat_1D_radial = gammat_radial.mean(axis=-1)"
    ]
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@@ -6064,7 +6068,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5589d279-b20a-4fd6-ae7d-f9ff3ccd6da5",
+   "id": "085bd120-6283-4d8f-adeb-bf4e2c781ba2",
    "metadata": {},
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    "source": []
@@ -6081,7 +6085,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 28,
    "id": "13660944",
    "metadata": {},
    "outputs": [
@@ -6089,9 +6093,9 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:190: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
       "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:191: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
       "  gammat_radial = _GT/_N\n"
      ]
     }
@@ -6108,13 +6112,15 @@
     "center_2 = R_mis*np.sin(_phi_Rmis)\n",
     "\n",
     "# get tangential and radial profiles\n",
-    "et_map, ex_map, radius_map, angle_map = mod.getTangetial(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
-    "kappa_radial, gammat_radial = mod.getRadial(radius_map,r_bins.value,angle_map,phi_bins,kappa_map,et_map)"
+    "et_map, ex_map, radius_map, angle_map = mod.getTangential(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
+    "kappa_radial, gammat_radial = mod.getRadial(radius_map,angle_map,\n",
+    "                                            r_bins.value,phi_bins,\n",
+    "                                            kappa_map,et_map)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 29,
    "id": "1cb19534",
    "metadata": {},
    "outputs": [],
@@ -6182,7 +6188,7 @@
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   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 30,
    "id": "32772d61",
    "metadata": {},
    "outputs": [
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\" 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+       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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
        "     <g id=\"line2d_1\">\n",
        "      <defs>\n",
-       "       <path id=\"m622cf3351d\" d=\"M 0 0 \n",
+       "       <path id=\"mb11692571e\" d=\"M 0 0 \n",
        "L 0 3.5 \n",
        "\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m622cf3351d\" x=\"33.431744\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb11692571e\" x=\"33.431744\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -6277,7 +6283,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m622cf3351d\" x=\"91.129354\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb11692571e\" x=\"91.129354\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -6318,7 +6324,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m622cf3351d\" x=\"148.826965\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb11692571e\" x=\"148.826965\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -6356,12 +6362,12 @@
        "    <g id=\"ytick_1\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <defs>\n",
-       "       <path id=\"mefd8ad2f15\" d=\"M 0 0 \n",
+       "       <path id=\"m05bf077e8b\" d=\"M 0 0 \n",
        "L -3.5 0 \n",
        "\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"33.2875\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"33.2875\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -6374,7 +6380,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"33.2875\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"33.2875\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -6405,7 +6411,7 @@
        "    <g id=\"ytick_3\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"33.2875\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"33.2875\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -6420,7 +6426,7 @@
        "    <g id=\"ytick_4\">\n",
        "     <g id=\"line2d_7\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"33.2875\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"33.2875\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -6469,7 +6475,7 @@
        "    <g id=\"ytick_5\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"33.2875\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"33.2875\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -6484,7 +6490,7 @@
        "    <g id=\"ytick_6\">\n",
        "     <g id=\"line2d_9\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"33.2875\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"33.2875\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_9\">\n",
@@ -6577,15 +6583,15 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p2780f8d806)\">\n",
+       "   <g clip-path=\"url(#p048fdff1f4)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
-       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\" id=\"imagebb348f2015\" transform=\"scale(1 -1) translate(0 -148.32)\" x=\"210.534559\" y=\"-21.704007\" width=\"148.32\" height=\"148.32\"/>\n",
+       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\" id=\"imagea81b59df13\" transform=\"scale(1 -1) translate(0 -148.32)\" x=\"210.534559\" y=\"-21.704007\" width=\"148.32\" height=\"148.32\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_3\">\n",
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m622cf3351d\" x=\"210.678803\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb11692571e\" x=\"210.678803\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_11\">\n",
@@ -6598,7 +6604,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_11\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m622cf3351d\" x=\"268.376413\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb11692571e\" x=\"268.376413\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_12\">\n",
@@ -6613,7 +6619,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_12\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m622cf3351d\" x=\"326.074023\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb11692571e\" x=\"326.074023\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_13\">\n",
@@ -6630,7 +6636,7 @@
        "    <g id=\"ytick_7\">\n",
        "     <g id=\"line2d_13\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"210.534559\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"210.534559\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_14\">\n",
@@ -6643,7 +6649,7 @@
        "    <g id=\"ytick_8\">\n",
        "     <g id=\"line2d_14\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"210.534559\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"210.534559\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_15\">\n",
@@ -6658,7 +6664,7 @@
        "    <g id=\"ytick_9\">\n",
        "     <g id=\"line2d_15\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"210.534559\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"210.534559\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_16\">\n",
@@ -6673,7 +6679,7 @@
        "    <g id=\"ytick_10\">\n",
        "     <g id=\"line2d_16\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"210.534559\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"210.534559\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_17\">\n",
@@ -6688,7 +6694,7 @@
        "    <g id=\"ytick_11\">\n",
        "     <g id=\"line2d_17\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"210.534559\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"210.534559\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_18\">\n",
@@ -6703,7 +6709,7 @@
        "    <g id=\"ytick_12\">\n",
        "     <g id=\"line2d_18\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"210.534559\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"210.534559\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_19\">\n",
@@ -6787,15 +6793,15 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#pd543542d08)\">\n",
+       "   <g clip-path=\"url(#pa224cf112a)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
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\" 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+       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\" 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        "   </g>\n",
        "   <g id=\"matplotlib.axis_5\">\n",
        "    <g id=\"xtick_7\">\n",
        "     <g id=\"line2d_19\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m622cf3351d\" x=\"387.925862\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb11692571e\" x=\"387.925862\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_21\">\n",
@@ -6808,7 +6814,7 @@
        "    <g id=\"xtick_8\">\n",
        "     <g id=\"line2d_20\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m622cf3351d\" x=\"445.623472\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb11692571e\" x=\"445.623472\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_22\">\n",
@@ -6823,7 +6829,7 @@
        "    <g id=\"xtick_9\">\n",
        "     <g id=\"line2d_21\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m622cf3351d\" x=\"503.321082\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb11692571e\" x=\"503.321082\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_23\">\n",
@@ -6840,7 +6846,7 @@
        "    <g id=\"ytick_13\">\n",
        "     <g id=\"line2d_22\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"387.781618\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"387.781618\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_24\">\n",
@@ -6853,7 +6859,7 @@
        "    <g id=\"ytick_14\">\n",
        "     <g id=\"line2d_23\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"387.781618\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"387.781618\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_25\">\n",
@@ -6868,7 +6874,7 @@
        "    <g id=\"ytick_15\">\n",
        "     <g id=\"line2d_24\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"387.781618\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"387.781618\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_26\">\n",
@@ -6883,7 +6889,7 @@
        "    <g id=\"ytick_16\">\n",
        "     <g id=\"line2d_25\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"387.781618\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"387.781618\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_27\">\n",
@@ -6898,7 +6904,7 @@
        "    <g id=\"ytick_17\">\n",
        "     <g id=\"line2d_26\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"387.781618\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"387.781618\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_28\">\n",
@@ -6913,7 +6919,7 @@
        "    <g id=\"ytick_18\">\n",
        "     <g id=\"line2d_27\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"387.781618\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"387.781618\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_29\">\n",
@@ -6963,15 +6969,15 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p3b79238b97)\">\n",
+       "   <g clip-path=\"url(#pf3a4b75527)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
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@@ -6984,7 +6990,7 @@
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        "      <g>\n",
-       "       <use xlink:href=\"#m622cf3351d\" x=\"91.129354\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb11692571e\" x=\"91.129354\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
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        "     <g id=\"text_32\">\n",
@@ -6999,7 +7005,7 @@
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        "      <g>\n",
-       "       <use xlink:href=\"#m622cf3351d\" x=\"148.826965\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb11692571e\" x=\"148.826965\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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        "     <g id=\"text_33\">\n",
@@ -7016,7 +7022,7 @@
        "    <g id=\"ytick_19\">\n",
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        "      <g>\n",
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+       "       <use xlink:href=\"#m05bf077e8b\" x=\"33.2875\" y=\"351.319763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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        "     <g id=\"text_34\">\n",
@@ -7029,7 +7035,7 @@
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        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"33.2875\" y=\"322.470958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"33.2875\" y=\"322.470958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
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        "     <g id=\"text_35\">\n",
@@ -7044,7 +7050,7 @@
        "    <g id=\"ytick_21\">\n",
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        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"33.2875\" y=\"293.622153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"33.2875\" y=\"293.622153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_36\">\n",
@@ -7059,7 +7065,7 @@
        "    <g id=\"ytick_22\">\n",
        "     <g id=\"line2d_34\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"33.2875\" y=\"264.773348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"33.2875\" y=\"264.773348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_37\">\n",
@@ -7074,7 +7080,7 @@
        "    <g id=\"ytick_23\">\n",
        "     <g id=\"line2d_35\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"33.2875\" y=\"235.924543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"33.2875\" y=\"235.924543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_38\">\n",
@@ -7089,7 +7095,7 @@
        "    <g id=\"ytick_24\">\n",
        "     <g id=\"line2d_36\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"33.2875\" y=\"207.075738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"33.2875\" y=\"207.075738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
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        "     <g id=\"text_39\">\n",
@@ -7166,15 +7172,15 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
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-       "   <g clip-path=\"url(#p8fd5121763)\">\n",
+       "   <g clip-path=\"url(#p4a7c1bc0a6)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
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\" 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\" id=\"imaged99be0992b\" transform=\"scale(1 -1) translate(0 -148.32)\" x=\"210.534559\" y=\"-203.144007\" width=\"148.32\" height=\"148.32\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_9\">\n",
        "    <g id=\"xtick_13\">\n",
        "     <g id=\"line2d_37\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m622cf3351d\" x=\"210.678803\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb11692571e\" x=\"210.678803\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_41\">\n",
@@ -7187,7 +7193,7 @@
        "    <g id=\"xtick_14\">\n",
        "     <g id=\"line2d_38\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m622cf3351d\" x=\"268.376413\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb11692571e\" x=\"268.376413\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_42\">\n",
@@ -7202,7 +7208,7 @@
        "    <g id=\"xtick_15\">\n",
        "     <g id=\"line2d_39\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m622cf3351d\" x=\"326.074023\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mb11692571e\" x=\"326.074023\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_43\">\n",
@@ -7219,7 +7225,7 @@
        "    <g id=\"ytick_25\">\n",
        "     <g id=\"line2d_40\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mefd8ad2f15\" x=\"210.534559\" y=\"351.319763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m05bf077e8b\" x=\"210.534559\" y=\"351.319763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_44\">\n",
@@ -7232,7 +7238,7 @@
        "    <g id=\"ytick_26\">\n",
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        "    <g id=\"xtick_1\">\n",
        "     <g id=\"line2d_1\">\n",
        "      <defs>\n",
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+       "   <g clip-path=\"url(#p2302090912)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
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        "   </g>\n",
        "   <g id=\"matplotlib.axis_3\">\n",
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_12\">\n",
        "      <g>\n",
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        "      <g>\n",
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        "    <g id=\"xtick_9\">\n",
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        "      <g>\n",
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        "    <g id=\"ytick_11\">\n",
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        "      <g>\n",
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        "     <g id=\"text_25\">\n",
@@ -8256,7 +8262,7 @@
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        "      <g>\n",
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        "     </g>\n",
        "     <g id=\"text_26\">\n",
@@ -8347,10 +8353,10 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
-       "  <clipPath id=\"p8cf2cc0681\">\n",
+       "  <clipPath id=\"p9ee3749321\">\n",
        "   <rect x=\"40.603125\" y=\"22.318125\" width=\"162.327273\" height=\"194.792727\"/>\n",
        "  </clipPath>\n",
-       "  <clipPath id=\"p805b1bab78\">\n",
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        "  </clipPath>\n",
        " </defs>\n",
@@ -8387,88 +8393,90 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 31,
    "id": "38b199f1",
    "metadata": {},
    "outputs": [],
    "source": [
     "# define miscentring distribution\n",
     "R_mis_max = 1 \n",
-    "N_R_mis = 15\n",
+    "N_R_mis   = 15\n",
     "R_mis_arr = np.insert(np.logspace(-2, np.log10(R_mis_max), N_R_mis-1), 0, 0)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 32,
    "id": "c17883c2",
-   "metadata": {},
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:165: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:248: RuntimeWarning: invalid value encountered in divide\n",
       "  angle = -np.sign(from_cent_2)*np.arccos(from_cent_1/np.sqrt(from_cent_1**2+from_cent_2**2))\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:190: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
       "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:191: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
       "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:190: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
       "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:191: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
       "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:190: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
       "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:191: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
       "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:190: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
       "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:191: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
       "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:190: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
       "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:191: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
       "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:190: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
       "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:191: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
       "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:190: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
       "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:191: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
       "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:190: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
       "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:191: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
       "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:190: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
       "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:191: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
       "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:190: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
       "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:191: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
       "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:190: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
       "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:191: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
       "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:190: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
       "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:191: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
       "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:190: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
       "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:191: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
       "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:190: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
       "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:191: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
       "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:190: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
       "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling.py:191: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
       "  gammat_radial = _GT/_N\n"
      ]
     }
@@ -8477,9 +8485,9 @@
     "et_map = np.zeros((N_R_mis,kappa_map.shape[0],kappa_map.shape[1]))\n",
     "ex_map = np.zeros(et_map.shape)\n",
     "radius_map = np.zeros(et_map.shape)\n",
-    "angle_map = np.zeros(et_map.shape)\n",
+    "angle_map  = np.zeros(et_map.shape)\n",
     "\n",
-    "kappa_radial = np.zeros((N_R_mis,N_r_bins,N_phi_bins))\n",
+    "kappa_radial  = np.zeros((N_R_mis,N_r_bins,N_phi_bins))\n",
     "gammat_radial = np.zeros(kappa_radial.shape)\n",
     "\n",
     "for j in range(len(R_mis_arr)):\n",
@@ -8490,15 +8498,16 @@
     "    center_1 = R_mis_arr[j]*np.cos(_phi_Rmis)\n",
     "    center_2 = R_mis_arr[j]*np.sin(_phi_Rmis)\n",
     "\n",
-    "    et_map[j], ex_map[j], radius_map[j], angle_map[j] = mod.getTangetial(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
+    "    et_map[j], ex_map[j], radius_map[j], angle_map[j] = mod.getTangential(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
     "\n",
-    "    kappa_radial[j], gammat_radial[j] = mod.getRadial(radius_map[j],r_bins.value,\n",
-    "                                                  angle_map[j],phi_bins,kappa_map,et_map[j])"
+    "    kappa_radial[j], gammat_radial[j] = mod.getRadial(radius_map[j],angle_map[j],\n",
+    "                                                      r_bins.value,phi_bins,\n",
+    "                                                      kappa_map,et_map[j])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 33,
    "id": "22ba0469",
    "metadata": {},
    "outputs": [
@@ -8513,7 +8522,7 @@
        "  <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2025-02-04T16:11:43.718622</dc:date>\n",
+       "    <dc:date>2025-02-06T12:33:35.708320</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -8544,20 +8553,20 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p9abeeaa8e7)\">\n",
+       "   <g clip-path=\"url(#pa99d65b8bc)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
-       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\" 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+       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        "   </g>\n",
        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
        "     <g id=\"line2d_1\">\n",
        "      <defs>\n",
-       "       <path id=\"mba4a50a40c\" d=\"M 0 0 \n",
+       "       <path id=\"ma7a60c1ff8\" d=\"M 0 0 \n",
        "L 0 3.5 \n",
        "\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mba4a50a40c\" x=\"33.431744\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"33.431744\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -8593,7 +8602,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mba4a50a40c\" x=\"91.129354\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"91.129354\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -8634,7 +8643,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mba4a50a40c\" x=\"148.826965\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"148.826965\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -8672,12 +8681,12 @@
        "    <g id=\"ytick_1\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <defs>\n",
-       "       <path id=\"mdeacede841\" d=\"M 0 0 \n",
+       "       <path id=\"mc74ca6bf58\" d=\"M 0 0 \n",
        "L -3.5 0 \n",
        "\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"33.2875\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -8690,7 +8699,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"33.2875\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -8721,7 +8730,7 @@
        "    <g id=\"ytick_3\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"33.2875\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -8736,7 +8745,7 @@
        "    <g id=\"ytick_4\">\n",
        "     <g id=\"line2d_7\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"33.2875\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -8785,7 +8794,7 @@
        "    <g id=\"ytick_5\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"33.2875\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -8800,7 +8809,7 @@
        "    <g id=\"ytick_6\">\n",
        "     <g id=\"line2d_9\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"33.2875\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_9\">\n",
@@ -8893,15 +8902,15 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p5bc62391ee)\">\n",
+       "   <g clip-path=\"url(#pdd8f556f29)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
-       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\" 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+       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\" id=\"image5f64d4d286\" transform=\"scale(1 -1) translate(0 -148.32)\" x=\"210.534559\" y=\"-21.704007\" width=\"148.32\" height=\"148.32\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_3\">\n",
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mba4a50a40c\" x=\"210.678803\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"210.678803\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_11\">\n",
@@ -8914,7 +8923,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_11\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mba4a50a40c\" x=\"268.376413\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"268.376413\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_12\">\n",
@@ -8929,7 +8938,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_12\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mba4a50a40c\" x=\"326.074023\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"326.074023\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_13\">\n",
@@ -8946,7 +8955,7 @@
        "    <g id=\"ytick_7\">\n",
        "     <g id=\"line2d_13\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"210.534559\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_14\">\n",
@@ -8959,7 +8968,7 @@
        "    <g id=\"ytick_8\">\n",
        "     <g id=\"line2d_14\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"210.534559\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_15\">\n",
@@ -8974,7 +8983,7 @@
        "    <g id=\"ytick_9\">\n",
        "     <g id=\"line2d_15\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"210.534559\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_16\">\n",
@@ -8989,7 +8998,7 @@
        "    <g id=\"ytick_10\">\n",
        "     <g id=\"line2d_16\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"210.534559\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_17\">\n",
@@ -9004,7 +9013,7 @@
        "    <g id=\"ytick_11\">\n",
        "     <g id=\"line2d_17\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"210.534559\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_18\">\n",
@@ -9019,7 +9028,7 @@
        "    <g id=\"ytick_12\">\n",
        "     <g id=\"line2d_18\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"210.534559\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_19\">\n",
@@ -9103,15 +9112,15 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#pcb1f009032)\">\n",
+       "   <g clip-path=\"url(#p142c2415fd)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
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\" id=\"imagee04623406d\" transform=\"scale(1 -1) translate(0 -148.32)\" x=\"387.781618\" y=\"-21.704007\" width=\"148.32\" height=\"148.32\"/>\n",
+       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c0Q7oLdedn9zBA6M5HKtwQEKlebdGbanPMY6FMTqCR2WBgWjZ1XSjrJIDogQeZL8ZoacoDlb9fBQ4fJ0RkL0PzxsFBnJmvT9TjcoNWKoWNWPZx5/TjXb9+A01QWsDY7RrTxtYo30DFjEooBiFgCUAEMw0CiBTZpyVf8Ndf2iiwDIAY5LtAaKWO8eYratzryjjwBF2Xpe51ll3zG758VbUqRElowECel5hAUzJbAt+zuTNNjeHGRjHANAwRkErCxPNNZUOhnyQhmRqmmEBSs441FRbyhIdmc5aBQBo25nPZSvHLTls0JfMtIps0aUKnGHnTzLwuTw1BsnNtVoewPsacjbigOcAxIMmpOu8nE83vukAIGjjQeXAM1tv1pGVAs1wNGUbChSGdZwqlh1FytrFRApBCZuCJ/7O9RgFSaWcyEzjykt0GQVHo1wf41QHdruxvrZQ92fi+ba5JmWkEtA40ATAlMpM3r+JAAIwA9Da+TxaA8a6JTYxslZRMmeRaKax/o0V+zYxWF4DDDY8RNmLyf7PdTvKTKuV7TT5t/k41af/cq5orvWyTk0VOu4abdTYKJhppahZDhrOdEva8SFpYy1gtDPddGBFC2UtlAZgQh+5QRy7IfoqKvVp8v8toAwBTAE4dOpoYRcCHnq9lLBagzwpyP8eHvQ9bbTKbdXFy2GLPHetL2eXGhs1gNejolI2sk0JNIvJxtpEHjgOQIBxx64ErLWw1kDZKS7JiXM6mdLU0WfBYy0/h5OrlPXDCjxYulbeUQPng6mYmWmvwjYDcmxU7VasU8i/Ypad5oooaLRaVgVw4HGD0wFIK4XZuJmcK7wpZyYHSo0YlqZzOQpI/JqVbzM7psmDAkW2WUgtBc9Gyeso1tnbVg6wvI4BttlDmsBZhyKzwZcP/MojfQg8HawTzTXq4fr6LaouhEi04kGjM9ahYNVWwVgVAeRTHdtoC60d68BMUNryEa/Mj0n/bAooBjjUPPPdEY9pN+4y2PJBXRn4TbYZNdFqZXJdSPul/JwcP4+zh/nWAg+WtDwQwPkz1ud3Va4RWPJvVmlwYKGAyUFkrMLk/5+NhtImljdWYZoMrNUw2npzLb8Af23hVGQZQM12OSbgApaxEJ9zag2YtU/DAzf4XPT/5HcmRfbh/J0jTLSD2QbggCMZ6L2ss6fJloOnmFZgHbTNtVYUjgIkyKTNAhoQIHkFjHJzN85Uc3KanE5ah3kdLE9pZQGrU8DQPwqakEb9IA+C6DIF8NCd9KzAVBMMQnbQ56Bi82SgYdrdbKL1sg0jnH4ixhGFIm9lspXa5Uw2f969PFZnnRwoknmgwDYBSBq2yTo0oBDaMVpDaetNtbSNJAwdAgHz8qcjcOyKbeIPBQei2B8CwJTOS9iGYxaAB0NedynfESaaoExJNqwcaD+50/xIlDrM3wEx2Qi7uC2dgmG21n1ZlLkAhoLHVq43N9Wo+ab9Y93A+Tra2shIAGAmhdkYzB48y0K0MHqQsI6eAT3bBTQhOJD5NrmJ5l6gU3z/xm6mNyjt/giWVZklfz7QEybKwdDwa4ZA023SdYzfTI4NRzeObwaegslmPZXmrBNAJHkxUxGAUNC4Y5OYdMYqGKtxpYwDYDbO/5mvwdcJ/eNVpxG0DDR6zsLQUTEQ0CyWa3hm1J6+3IBP6syBVMqT1XFT0IywTYeIgcN2ds0HER7fEjzUZAvploSTc9YJ684M3NIZY92KgFwoOAJoTnpeMY9jHQNttDPZZtfGPBlcZwM9GSitE3OHBgQ0NdGulvg3C+Mkg1ApQAezNHZJch/ZwUsGPss2DPusggakrrSdOwENxzYd4OKBU6Hzdd7PEDyUgRDMOCQRtpx1AojcawLra059GxNBc1IGWtFImsZJGVytiW0bq3CZNK6TxlUjrTtE1Dzb6CugrwQ8WVAA/rIdYDxKgrqFqJlV3kzjBj1hGNZcK53/kYCmxFRdplqR4qXgoQpmxyvwhHN5udBekhFZJisCT8lkA5aN0sP/lHWUdSsBFJZ5mhA9oyZbAM05MdlmBxSrl+ABFC5G4zJP0Npg1lPUP/g1Dijhz2K62GTyM3aNBqz2W0tp3wd2AYdViH8UHLH7yLk8H2eiiUDTAAx7Lv+N7G43AJPUmeQb92uolIFTYJ1N4OHSyHHYdHwX9tkIHuvLWb9nrSWmW2Adq2yMmAHOh6E6UtCc9RyDAgYKJ6swkajbZZrwrM0SIKD9Yzy7ENCE42QFtAr/WNhs2fbqaU6AQdkmAccG0Lwmy6zqjfkKoOlkG2AwONANnly5m7FPbr8skGmBxxj4NzZ1fAkN2viwsk1Yx1gFo3zImTAPgAiak3I+z+RenMYM7UAFB76r0Xg+T3i+nHDRp4VxCNNMFwtN/lxQwF+jZ5O4b2hgGxQGdQ4M7f7C7+R/CWjyc+5G3gfLeF349EL+htSBU/F1usBTqqtizrHs48+J2WeFTJcWwWPpALCI78T4pBw81irMAODXm2nlwDZ7Z994s81YFQEELObbWc04ewAZq3BRU/R/rkbjeT7hh8lATRbGBy2U8cC5uL/pxUK/WB+SXq7XTgB0/i2e9QCnYAhmXUgrgSZOmuagQ+l4gGV6AFNI2xM0NbYBNoajq+AJGZL0UFCQRtjHVZmZb73sY6k+yzc6OfYJz20NvzuNQjhy79F4vcIqAKVNBI+2FsZqGGtgrIZ7CweYYBxwtAMPAMxW41FfoZXFxWp8ms94PM34qP0qAu/jqKtjmOnFYnq20C/GR9L8ANWhj0iHZEwRALIAxploFCiUdWJaD8vck1kGoOrPDDJNkDZwKqwDLLrtDqDsyZkAiOsPKYBAWClAxfqdaQj7KK0iQKANjFGgizODt0K/Bql8KPqqLLRx0TPKPpR1AngudsLk872YE75/fsJ0mnH1qga2OT1bTJ8MpucZ6uKAAzhAKCzgoQM+giX+75gppvnfIIAqmmj0N7jjsll2NwxTqltaLxEZ4zTAA1TYh2pSAhBQBEySRgDkqm2AiANQdOADgJQnpAxAWEw369lktu4NTifavxrA3yStLK7W4GI1TlZhhnbBAwBnNeNRX6K/86gvAIBnc8L7hzd4f3qDZ+VDzdcAGovTxxn6eYa+muXyTho2TC4p5VlkAYqZHEDMREAzLeeRMc2KZSiIQt/2AuYW7OJ1qcpOoAG69lVrN1xln/xEDwuF9AILuaxMp+UACuYaAUxMywAEq9xGGv6cUW5S1FjrX0BzkTernb9ymrKm5yU4MCmLszK4qAmzdxgmGDzpC85qxlv7jAkWs9X43eMb/OP5HX7QzkybXixOnyxOH2ZMHy7QLzNgLazWUCcXgrBKLWA4OYCYk2cUCpopBU0CngAS329WLemxLzmTrJNdRsCyqjfJ3wBLpU5xG4x07jkgUySfv+PrKoCIs67ydCmIKNg5For+koomWlh3YyOolEv378oopdzKY2tgzAStrXs1AHCTmZOKvy3RKSzBedRXXKxD2VnNeFIXnPUVT5513j+8xT88/AG+myzUrDA9W5w+GJw+XKA/XKDm2dHeCbDQnl1cu+asYE4Ks//fnEDAowjjZAxDAZOZabnTL2aX12SWQp0l6QFMkPG9owGRct0gWhWi6Uwa1yZRjAURrSxeywIaCqI4gHzUzipAaUDZyS/Lce/TaO1WOc/GuLVn0+LfhEgbEBjI4FFf8NY+46yveKef8Q7PeFAzPpgH/N3TN/j1ZKBm4PTR4vz9BdP3n4AXBy6cT7D6BHPSsGcN86BhHhTmhwU85gQCHAUzITHLKGCSgIDKf9sV6yS3TGKG3YJVKvWWZAQwQbZv1hGkE0SxCq5cCUglf6bmC0afxuVjJ1cDMCiIoJaBEgeRZx+/sYbbZGOC0f71Am0xa43ZaFxng8uk3YqAacLVaFyNxsUuvs4Eiyd9wTs84yv9CV/pT3h5nPCrNz/D/z7/MfQVePx+xun9J6jff3BqP55hpwn2cYJ5mnB9mjA/aQ8aYD4r2Agalfg2ETjhmhh2ScAyyip3xijidjtkv9XRJROrISIwla62FBzI2YUJb1PAJV+Oo6ZbzqwePJawkfJvbhr/W2mL+aqhJ4Pr5JbRPGvjJjfnEz7NZ7yYE57NKfo7D2rGO/WCb6dP+Pfn3+Af3n2D//X4S0yfgIfvXqB/+z3sywXq7RPwcIb5yQOub8+4vp1wfeOYZn5wgJnPivgzC2ho1GwNmjVQ9gLJZoBwbXTIXkDJ5bhXp2t90riYVn8ubkqlomTeJtMnYylVfA/FhgzZOc88yjnmy2/XptEWSrsFm9ovo3m+uMnNx9OM75+f8P7hDX73+AbvH97ig3nAy+OEJ/Ub/Gy64D+/+RX+x7v/hOff/xTn//tb2B9+gHr3Duard7h+/YTLT8+4vtW4PilcHx3TGA8YcwKgXUAg8WFKjFIBSREgUnDcABjV9g+U19k7WtifUSouUL0dRf8rt19YLZt8NWA1cFQKrAxw1q9ydgs2LS76BDVZfNQW02nG+5OLnv3Dwx/g756+wa/e/Ay/fvuv8F/e/g1+efqA//jN/8Nf/+ZnsN+9h/r2a1x+8Q2ev33Ey1fascwjIsuYE+/0I+pBuoP6KcVrW3Vhu7+yvtsirwGEXlH/9s//rHcY//hkD6cyH0zMU9x6ZorBBw1AW6iTgT4bPDxc8c1PPuBPv/4Nns0J/+fP/gPUbPHhDydcvnJgMSe4kLO2azZh2l3pWnhIbL7+f2Fy6n76/wiFLssX5Wf9Ks2ft8v/KhxbkLc6VVzIOX0Cnn//Ff7mNz+DOSn8u//2l3jUM/7ytz/Hxx/e4Pn5DHPRsLMGZuU/iaCWOmmAg9MBYEd990r7L2Pmzj/z4WXzKxSt8pLBxAxERY/9XGn6Wy2vNZPdaPQVUFfEtWenjxaP3894+O7F+TTfvccP//VP8ahn/Pd//T/xqz98i7/4+Ev89Yc/xq8/fI33n97gh5czni9nXK8a83WCMQrWKNjZOy0ZqJZJ4CWgEpcxlUBW6rsG5Rx+v+5AXgU4N+vYwg2WgALIgEH+ZwFCmIT+r2f492kCYCymF7oiwOD8/QWn959c9OyHH6C+/Ro//HzCX/725/jVH77Fvzl9wLu3f4VfnH+Lv336I/z9p2/xTy/v8P75DT5cHvDxcsbLdcJ11rheJ1ijYIyGNYA1DkjufywgsnDLhWgfra6zEErLlxnlh5LgDZHV/eg1BV8BaIcBZxM4NgKDbb9yrLj0HCQ+rQUUFcywbH+A5dUAu6w9+zDj9MFNbqrff3Ah53fvcPnFN7j8ROHjD2/wFx9/iXdv/wpv9RV/cvoOD2rGW/2Cr88/xT+ef4LfXd7g+5cnfLye8el6wst1wmWeMM8a86xhZjdvFICzBpJNmYn0qw2rK/L+ygGVh/7pTajdy1LwJpPmWKqVPwhUuwFnGCiScj0A4ersAUmWngOFmmQ5WGCQbaxhF7PsYuP7NNMng9OnGdMPbhlNWBGg3j7BfPUOz98+Yn4Cnp/P+OsPf4xfnH+LPzl9B60MvtIf8fPzewDwKxCueNBX/PPlER+mB3yaznieJ89Ak9s9Z9bRlAsgUhREOXjoH53XCt0S3ytfOpSbH2OPad+XBk12v7nbLx5vrYjqoGx+H6dL9jaxSvUKgRLrZFmGB0sEDIiDT74aoOkWTmSPAPo+zfQ8Q3+aoV9mt/YMgH08Aw9nXL9+wstX2i2ZuWj8+sPX+NunP8KDmvGV/ggAeFIXfDV9xOyvTvtFpCft/s7zCc/6hJfZ4DJrXLUDkDEq/lmjXVTOWsCoyDx2BR61mGax37J5LQskK9VVxkrc/eJOx/Il26+aJBuPJXbslOFXp8VyY0YB+lklpgewhHSGXQACFGqWRaaxxEQjewRc/JubLwbqYtyrAda6BZsPZ1itYX7y4CY337j5GTtrvP/0Bn//6Vu81S/4+fk9HtSM2eq4QPStfsE86WQt3LKvm8WkNS7aOv/HaJjAQMo4rBi9YCOCKBxnoAmsREFC2YiwC12tnn9FeyUEcKu05KaRNrlq6LRbD4gGANS9y41INoBlhFUAIbNk5xS5+St2Afx3Z5YycSum1RcDFpYJZlrY9yxsrKEv/nVnY8lLaH6Vs9awj5NfRqMxP8J9fGpW+OHljH96eYevzz8FAHw1fcRZzckKa/d+zxVm0skr20pZqPkEBcR93K4+3fgAglHGRePCam5lF7/HLLiJIAoAiiCxy3l6I0ogysy+oo9UM7EEK4e7QDQAoK4NCZvSynMLZiG/W+yy/EYGpIxhyHH+Uad8A3R208AryRded1bw79NomJN2CzbfTrg++XVn2gIGeL6c8f75Df7x/BNMymCGwpNyPtHs3z6dlHst+6JnPNgrZuteMwCQvNoAuE+VXGeNWSn/5Tn3rpExbvMRY9UCEhUYyAEqYaEw4EsstLpBoWsHQETrysdEB4hEABKCR7zpelNqeXrYpZG2qknILjGdAUx+rPL/KWgo49CPOjHb0i67bFrQ+ROrlXtz0/+2Z43rk1uweX30Zpp2ul6vGv/88ojfXd7gUV8BAG/1S/LqdZAJJr40d1UGJzVHAOWijIKrze+boPzmJNb6T8mHvrLR74m7MlDA0OP8plQAFP2ieM/UGhwtJiqBqAKgvcAj+rBUVY4CTCe7JPVygPH68OHl7DfWLEPZZmEc5lMb8UNPNqkjXETcI2BaXnM2Dzp5NcCcEG/gfJ3wfD3h+5cnPPiNPebJ+TiTj1JQ8CQbImrjNg3RCieojH3c5iMzPOv4PRWMUYB2n1w0AJReGMbGPlo21UpNtoJ9ldhNWAsBEctCtFwPC1WCCtVxLQDPfu/jJOkHMcxWwIRzmVm2Ag3xbVYmWsxPWCWetyu2WpR0q5cBLLvSTP7NzYfl1QBzJts1WcAYhZfrhI/XM/758oiz39jjUV8j6wAOPDPZOMRtw6vj/5NyADJWYfIftzJ+N1GLsJeC23zEfWJx2QgUiLu1wXrFwhcfwsaNscPpcX6zOADZ9HcCoJCvBZZBAG2Za6wCp1rxEaCRmGTkd2lNWDyXm2X+fI1lSiYaSFr+zc1k/2YWNF4VrcgSfgcQc1aRaWx8Y9OPJz/ncp01Pl1P+DA94BQG/aRx0XOywWFpPzf6N2kDM7u3VydtARjA6Mg8YfNFt58cuQ/RPFvYJzHfSjQRTlnfwfn4UGn2BWMMA+VgWQGFSUOhXTTA02Cdba9Oc5rk7XcCBjiOZeL5AdDkjLOqI2/fX4Rb++mHV3gaKzgz7eQ21TBnt0+A2ysACePYWeF6dROan6YzTv7LbwYKD/aKSS3f23F7UE8xNL3aVZQAyT1X3D4KVlm3jW8EDQMeG77swLPP4vTXvH1yowTsA69jwj7kXDf77Mg8ReCIw8JUA0kdR7OM12UX0JD05bdNjlkwkwtyZlk6gOi+ZmFjjcA20MjGnmOdyzzheZ5wnk9xs/bZqmxDd8QN3U3yzUIXjp7Jb2NV/AR9fE/Phs+g0P8RIdIET2AVyjTwA5Z2wxb2yfNxx8W0TvBUWGdslxuu5bzNBqscxTKrfLZwXABNKz1nm+XPLiqEP7/FU9xm1l+oVQ48blONdGMNQ15Gg4WzpPyk5ct1wrM+LQwzKVzjJ0XST4lc/d4G1HwLGyYahnVmi5jm8tL/F4i0wOO6iAFPuPhEbsA+QvD0CgucLur6jEGT1M0BZQUiwjb5JflXqMMDF8qbLwEwYSypBUjhVeewsYadQllLK4Y1wDxrXOcJL7NJviN6UrM333T8eBUAso+1jsf5nE68/ox1LAJgrH+tPININtApeNKwVcHH2cg+KgdaDSxC8PSyTt+GhKu0+wZNUhcz4HMQqSwfyzaMxE73TGMBH5JSSZnARnSHzdWmgWFjDfIEtUbBzG73nMusMWkNNZ/iPm7GmuJnE/PtqUx2z5QfRFphxTrLN1Dd6AmAUcDCOnapp2m2fa7gYWTX1wruDTScH9I0xbg6KpKAJhsT6c1GyjjJDptks0C/jRPVI6xqnv2CzYu2Sd8ZrXzoOQ0UAEhBE0yphqkSx7JnnQiYir+TmkyfCXg2yLavTnflTw9vBhqsjzkw5Gyz1qXS6xE0Pr6klroS9iBmmolMo6JfE/0jKr4C61c1uz3bdMIuJyhMhHHoZ+IDaOL3TCv3jX73NP+dsw7tuMTfIabaq4OnJRv8Hfmm6wIdpGW2gKbYLlfWp7OsUWIbro6C5OziTBg6QMg3NyPbYNmRxv+BbBYY8uW6RuYx7iNUYW9qwIHCsY5jHDcnQz/+u4AmfHO0BqDYB2oNlBXrcGWiverz54O+NMD3AE+pDHfMiNRcWwFHZOPlndlhog2BhmuL6sDlr5loLZF0bpYvfgHNDwzlGShlGw8e5qsB6101A13ZBTRWxVXNV7gFm0HCigD6leuQHv7PQVALGARJBn4xU9lkS4IFyZOmkIbsXJKW1c+Bp9dkk7AOo9/xew502pUldkjO5SYal6dRHxdJ4yJusYjfbD2tfHmARhVUei+obxPBQ0GTm2nKpk8Xi7W5Nmso5d6xCRJWBIQJTkMuPDfTDMMUNF8uSuWjNQtPM/lpXRF8tGNaJtsW2dmf4UT2YankuJNtaN5SvgpYRH5NrkuBbTZLbqZn1cdjSoYRENRUYz61QRhpJZ5xlAWsf4fGGOVeDfCLM4FgJjlgaOaJEf0dpGab+39Lx/jrDxYawzpVk+0If6dUhj1O25GYa8cyzo4mmrQdKiL2GZD8HtOI2lqJjG1UFkFT6W/iHnidw54ADjzudWc3KaoU/KsB7rOJk9/HOgCIExoskJhqYskGH+cfcfl663Vp6DfZdpZ9gbNB0SETrcZUJenRcWWKeUueM9fzZqhvE4FT+BJalm+tc/B1HIgC67jJSbdA0zGMcSalsssylaxjqdm2/EZ8AzSYcT2Aao7R2uA/0mTrUrJPjtuso5Ntqmm9ujTaqOodfBMun+LBA/AP0cW/UZFZ4C2rHDzW+zfUtFOWmDeBeYwLOFjj3twEAKW8n2G0ZxxEAJWe7hxouDzW1kHEMkuBEUSBBraRA1hnI5A616pVnkJHs02pvR2fIiXbNomiUfDUmg+ACb8zPyb/1iYbhk6UQGSeMJiNUf7NTQWt3fetwytts3UDVRfqDD6NTZiHDxqEfBKRRuGK0TTgdVin04SsA2dUaUm5XrbhImmV8t3+DNOpFDAceEI5Gm2LYAl1qgUouT9D/Zrkj7uu+BfA4/cIMEB4m1MpFd/eXFZQe1WYKBv9TUFTZiBGt4okbFQbmLm5xuZpsE5RCUEeRloBgmFTTTowi2ZaTXpvUGf+vFNWnbQ4NctxZpql9TGp1LeJPk4GGhAGUmnZpfL0t7VwG2go92qAtja+9hzeownBAQqgEmPQSFuejzPTWsct6TbXpAO/ZK7tUTcjr77pem3QNwGxB41nnZeASBFfh4AnFCuqRZiDggYUQCumsQ3GURnz+GCB0YA2MdKmtYmVhKwtCzD+JhE3OrjXYKlUKJWWabS3mbazJMAZDtf2luvOn5lpR3Uo53CqNCmqVKsDKTA48IQ8lJWaD0mPhGSbJoVosrk3NnV8TSAQoQVW0bVYJWO2xT0IM/Y5RHJ/pjtcjb7xMArIrFzHawXCi6F+RiG9Ve5Q4cABwjQMy6zYpvAYT5x9/38OmoRt8mU24LvBvSNjUz/HIA4y46sK4KG2pns1AOQVAUZvBiAc+yTMQ8skdbFN7CMdLDU0p9MB2lc31VZyIwDlJln0YRggiVTMfJTcv0lYZWWu2aSO5N5RllWITBN9HVgoreJpYxDZRoWQdIgAehCtrqdgltXYKD9/qNyh2Xb83tE3qEcqbKSEYZXlee2ztBwF7kHMgUaTPHkZyRgM5hk5jns++wrcZaR0SdnG2rXZVnL41+yTX2Sm2+cog6C8P8bZSarhxJxhOPAwJhrAg4iLiHE+TjyfMxLSc+uLIfrFY7/QMvg98boUAx6iWEFKAYASaGI6Wxlf549JtgPn6MDAVsmeKK34PAueWLjwYC2xB2OyrUFk1wCqSRYYCKyjvHLW2+kBPIt5Ri+ab2z1oTXGPOMLCvMdJb2ssYPpdxvGGVDycDOuBJAOpgnCBQViOgEFB6KhhzIJEgTWcS+P+TUNBDwuu838m3LnFkPPnL8zoPrhciN/6LBFnltJuskMXN6GyVXKzwUKREwTpACY+Duc49iGnLMk3QY9PLvEVdJQS/SHsE6w11wOBx7rwUMBlCrMy4o5aqBZmXJpPthCvhvIkaulP08fJwPIiJT8mBX7AK1xxoIk911Yk43LK1J+0TuyDhaTLYDH6bRc3BpArXbWgAnN5+e7JQfWZyafJ3Ak0mAdgD/HAqghualWAk3MU8jXbggpqKPegYUQIEQw70030mDPcF+ZbvEHBVV6csU2P0IpA+cOL7pmvtUAEqUFHmAFoFg0M/VW9XLnKGhWvo7lzbeSJDpSmvTBBRtYJvJPmk5fbssuoLQANG+eu8gcNHxhgZn2mY23z59xBEBhfRgiRZYRgmV1Pvd1MgCx9ZXaCXrkTEN/e9YJkEnAE7MtF5nH10RgYZTjQCNimx9BmPr+gMMBoXdJeY1ZKmUTAIV8FamFpkugiWwDcly5lKRqm5ldsV8WhVfgiSZcyKFohbIHfQkwmeIsAGtsw6ZxdTQ1vLncH3AawtJnjVky/6UFnpCvW3ImycyzJR95yzMrKxIueIG0U3KzzeWwSRG3JXTfha6jbfScWqdXgFSq53MR3c4yJklfDA6S5n0V3peaD9I1aEs6tEBTAFEXgApP+SQthK9pA5zDbgGb/bFNlvKEtmI+BjRZPdXrYRtvnC/lJb9F7+QMSplxaqbQTtIzV9O3MpYJFGTnQ5XxXFRKokt6yE2AsqDJ9hQo1plaU0tdKx+scIEkrqZIemQfZdPrVGXwLG0xSasnQa5bDrgR2/f15JA3QPmWMA620hhgRGpysfUCZQDRPAJhw8kCpsn16+my+IpBk51cJ9GoWgBeuic0uu9ZFTCAACCVstW8G4C1MwncvY+TgmSAdUI60ARQaKKmC9sm+T8HDa2YDRis6itELfL0yKjMEycmZeCJBZEAKDZduXje8Wf0TMqUz63rqpt79ybbgXMDk46TIuuUwJPnC8dI00QPtYJZxYEmMdEaUs2Tm2mlPDXwRKDFzMk1iFczN6JhtSU7XWxzlOzQ7uswTo0ZWgAgrCMtG4rFcwAPoN5rCFXlQMpAk59LmCcrU5VIFmRtAGWdeG1l8AAZgHJ/p1dqLJOfL4GmNw8KeW4otwPOQcwkAc8qXzgfTwob46yVzFRbmWwgQDlauIcDBQ+Qsk9UDvGcrJ31xfCRsxszzQ1BNAQcaTRMYl2spJN11ufADyBUxkinksVVBCs/x67Y6LDAEe0EwjIJeNSSjw50FkTSZluAifowv/O8vWxTEXEoehBs+8/jSK+xZOpUJB2EtnKOaSu/l2r5k7a9yk/rZUBTbJ+aaYOiwhxNPsC4ARfSLM2X+iS1+Zxcivm5Dh0BjVSkZQ5gotv6OFJzrWJypfkazIOsLJeGzgdaiW1oPeH9flU4n5fvaT+/vlae0CmJ2UbORT28zkMDmLNhW8eVCxhhmxv7OvswjrAPatKa6yjmqzFPKFtK62HHAmuENlnQ0Lw1fTi9OWHNIpQHms3SaF6WrbZSMFMvp3cPKw1I1UzbCWByxunYc0peJypsUj63dvQrzEPrA1Nn7yUxJl/UYZWGBFxJObbuyl1lLipZ9LlSikTVKLtQ9qGKqLx8p5RU7wHNquzxABC3l0nCOLvhQsgeuRSdbqachHmqppGUcQr5OZZJ9GJNOKbuUWk91Wlaye/Jn/SWSa+1X8vPMk8DNKMBgSr45NX0tDHs40gja6HNYjdkzFKtt5U3e9Mx+8nX23N/WCBWTLNWmuQYDNnnHZpHzoJCNd+GW26T19krRdYZ8IFG2kFHNK23zUz2Cw7UzK5W3h6TjQEP0AZQfrhhymJVQQ003Lk9rYyiuRYa50yz3HQDOZfp2pReU6vGjLVyxbyV9iVtD8pxUbUeIGXCTlY2gMb7NTyACkltYQaoCDQlk3FEFw4E9PeKjSrgyRsvgahXShe0FTTdeuxXVS514GwY/LmszDUBk4yuMysCiGaSSuFpXo2agQENxzZbfZx4vWEvNbTBA6R9WQoKiN/3YMpyuorSGh3SYJs9379pXX4f47SiVy0wYGfwFNKKAComykUSwGjev4qvtCrP+S0onK9J7tfkD568jj0GYdHn4dJ2Bk3LpNvIdPf3WoEEPMAacHkatj1AS/Ws2syOq6abtO6mQuv2m6wTGsuDArX+HJGqz8OlCRo70OQalZsDp8k6XBnWf2HKFQAU6thFKozTjKzV0kekxDYt8ABlANG0vaQn2jZQ35GvSJfk+LVqkmsSlOlarqIq50akVF8LNEQOfWj6ytkBJB20lvztpVOpvq4VCo3jvcp0Sj9wWktc2DLpIXsd3KDMy5X6uwYShTEg1cpk6c1AAXcuqc/Wz5MsrYhVBI9dn1uXKXToCIgs2uV6ASMAQNO3KdWd69Upx5hqEvMLzDjpcP6rk5m1trewEAPk4vlaO9IgQk1q5lieJ/+9yleJpuzxtO69UGEUTmSiHUT1bcaR6DZijkHIPKWytYfXXqZaha2koGmyzZ7CmWwS5onnVfq3SZfBeraAZoRtGJEEkm47AcqxBzqYB+v0auiZlttJqoDJjmsPhl382QrrpLt+Yt1/kvZv6XR3hK7FoDnQsRwLDrRm0DtFzDyV9L0elF11S0FTNdsG7q5wsrHIPNzxa8pW0GxpZ7C+FXB2HXhCswuogKc3GIDtFkezPNe+BDQCv6cmVYwVTLImeF4TQMWoG59eBM3RbMPUJTPVWNPJrkZV13xLwQ9lu6YUbKCZKx112BwOk1ZUg47fPR9OggDAymzL9Oky37ZK08/ikzeDRsg2UgPgsL2jE9nKPCF/64m9R0Cgp94WaFq67L6coayMKGy791xOT72V86/GNBXZPThQDRV3ME84zdZDM9XycJXWRAo6iW9airK1xntJ91q5Eutk5VavINQ6usXwNV16pJK/+xXoDl9pq3S8Os0oUHiduhs8YNIhBFChbDX/iPT6Znu1OyIN8ADgAQS0AbqHNOoZ2jOgO33cTAP2MNV6zY3OaBkguF+vYaahMxqI7F7l20dJVUqCABXHP2mYq6dyUa9lrmFn0BTr2T5QWMYpMkaHVOtoOfsV9qHZinWzCtUKtSoVVNXwgW4yJVILFDD0zbJPXl8uresYGDfNEHPnQ2GLLtI6Ot/HKVTUa7LV6mqdQweI8jo3SPUedAQ/3LkdH+e1TuZ8IyaNDtwiiGj5HWSXnTZHzhXa7b0lO+45cAB4YiXlZodAJBSRiShIr46RAaWrO3VxTMOBp9B2F4g6ZddtaXcEzYj0A6fBBpw0wYNGnZI8wip6y3VVxkXb8rSdB2NsJHf2JfM01ehLeaDXALX7zH5vniFTsb/Mzl9kKz8KxWvKpKO/F7x92dvtC851r2+UhpxFlTH5S3U0AJTLri+OSW/MVsDs7GQWo2rD5kUDvk39pdExlf0dIZI2Cuf4pTpZ32zQe9XNPQsfa9Gpo6Jqo21I8m0AjXgZUyYHvY9TM8IF7APsN09z1ByPNOwc8x81ErOGpZt5SFhG4n/2lJPKXiwEHBbOHAdOy9ep7GkWRASg0FYsJNCtVHYP6QUMwF/gDnqxz6cSeEptdpppSZk9pafOnQCz5VlWnQAVmVUtEWjXtYr5FibaQHtbQSO6fq4q1hwrVNYyS44207a2JzbvdgBN4/xtPp4rYB96uutJsMVEk9ZVkboveIsRWJBSKFPKMOx83YgeA2VG6xA+ffe4LU3giFYRSEPUwk+F5FmGLvRANpK9Kl5Q+gC9it3amhzt1elWz4GRdvYEjSDP7TddH9iOdhcgbRS5KVlRrmRBbQ0zowGell4jINpTRu9np+O/57gRAUe8dk04Ubnkl5lwnD616rbKUCCm1fgNBmR9RYHQDt7LRJPWPVTPgYAR5hUzTtfCz1EA0cYG5CYLKXORdMpIUKEmlcnQpjU84ki+oqvm2h+7sd0P0o78XaZa96rpXgDFcvsA6RDp6YBXUltE5Pdg/5Zk4/0eupTOMt0+ztArB1vmYYCKg3vwyNwymASqbVK/wjpRBVkspqzM0WDa8f5tUnWg7FBwYNP7OltBlNR1R09JoIthdhkzQvAMt3lPTM/ILrd/sI5N3wAFNiq/mvXeUNdryd5zP92VyXXYBKI7kF2fkxvr2hyO3gVAQUbWTd1SNg62wwbrwLIZdm70DsB0uBGxU/27zePQTj/k4rf6A3vW19v8rdoaWXdGZK9NRe/Ngj7ioXvI6ui768xXepK+2hN8I4B65F8CSDi52RfZjp60fG25BzNnJa/MtIfKK4+bV/8G6OiAuxXg7hIQW6R3Evto+UwfnK8OnFH50Q3oe5PPdEDfSm6zd/QX+SI/MvkCnC/yRQbk/wNLG8CmqcqpQgAAAABJRU5ErkJggg==\" id=\"image8395a1e639\" transform=\"scale(1 -1) translate(0 -148.32)\" x=\"387.781618\" y=\"-21.704007\" width=\"148.32\" height=\"148.32\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_5\">\n",
        "    <g id=\"xtick_7\">\n",
        "     <g id=\"line2d_19\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mba4a50a40c\" x=\"387.925862\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"387.925862\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_21\">\n",
@@ -9124,7 +9133,7 @@
        "    <g id=\"xtick_8\">\n",
        "     <g id=\"line2d_20\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mba4a50a40c\" x=\"445.623472\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"445.623472\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_22\">\n",
@@ -9139,7 +9148,7 @@
        "    <g id=\"xtick_9\">\n",
        "     <g id=\"line2d_21\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mba4a50a40c\" x=\"503.321082\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"503.321082\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_23\">\n",
@@ -9156,7 +9165,7 @@
        "    <g id=\"ytick_13\">\n",
        "     <g id=\"line2d_22\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"387.781618\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"387.781618\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_24\">\n",
@@ -9169,7 +9178,7 @@
        "    <g id=\"ytick_14\">\n",
        "     <g id=\"line2d_23\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"387.781618\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"387.781618\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_25\">\n",
@@ -9184,7 +9193,7 @@
        "    <g id=\"ytick_15\">\n",
        "     <g id=\"line2d_24\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"387.781618\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"387.781618\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_26\">\n",
@@ -9199,7 +9208,7 @@
        "    <g id=\"ytick_16\">\n",
        "     <g id=\"line2d_25\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"387.781618\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"387.781618\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_27\">\n",
@@ -9214,7 +9223,7 @@
        "    <g id=\"ytick_17\">\n",
        "     <g id=\"line2d_26\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"387.781618\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"387.781618\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_28\">\n",
@@ -9229,7 +9238,7 @@
        "    <g id=\"ytick_18\">\n",
        "     <g id=\"line2d_27\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"387.781618\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"387.781618\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_29\">\n",
@@ -9279,15 +9288,15 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p69b252afe9)\">\n",
+       "   <g clip-path=\"url(#p5e41af0ce7)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
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\" 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        "   </g>\n",
        "   <g id=\"matplotlib.axis_7\">\n",
        "    <g id=\"xtick_10\">\n",
        "     <g id=\"line2d_28\">\n",
        "      <g>\n",
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+       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"33.431744\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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@@ -9300,7 +9309,7 @@
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        "     <g id=\"line2d_29\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mba4a50a40c\" x=\"91.129354\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"91.129354\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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@@ -9315,7 +9324,7 @@
        "    <g id=\"xtick_12\">\n",
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        "      <g>\n",
-       "       <use xlink:href=\"#mba4a50a40c\" x=\"148.826965\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"148.826965\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
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        "     <g id=\"text_33\">\n",
@@ -9332,7 +9341,7 @@
        "    <g id=\"ytick_19\">\n",
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        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"33.2875\" y=\"351.319763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"351.319763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
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        "     <g id=\"text_34\">\n",
@@ -9345,7 +9354,7 @@
        "    <g id=\"ytick_20\">\n",
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        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"33.2875\" y=\"322.470958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"322.470958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_35\">\n",
@@ -9360,7 +9369,7 @@
        "    <g id=\"ytick_21\">\n",
        "     <g id=\"line2d_33\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"33.2875\" y=\"293.622153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"293.622153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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        "     </g>\n",
        "     <g id=\"text_36\">\n",
@@ -9375,7 +9384,7 @@
        "    <g id=\"ytick_22\">\n",
        "     <g id=\"line2d_34\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"33.2875\" y=\"264.773348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"264.773348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_37\">\n",
@@ -9390,7 +9399,7 @@
        "    <g id=\"ytick_23\">\n",
        "     <g id=\"line2d_35\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"33.2875\" y=\"235.924543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"235.924543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
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        "     <g id=\"text_38\">\n",
@@ -9405,7 +9414,7 @@
        "    <g id=\"ytick_24\">\n",
        "     <g id=\"line2d_36\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mdeacede841\" x=\"33.2875\" y=\"207.075738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"207.075738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_39\">\n",
@@ -9482,15 +9491,15 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p1bc1f1145d)\">\n",
+       "   <g clip-path=\"url(#p56b7f0f743)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
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\" 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        "   </g>\n",
        "   <g id=\"matplotlib.axis_9\">\n",
        "    <g id=\"xtick_13\">\n",
        "     <g id=\"line2d_37\">\n",
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@@ -9503,7 +9512,7 @@
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+       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"268.376413\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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@@ -9518,7 +9527,7 @@
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+       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"326.074023\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"322.470958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"293.622153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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@@ -9593,7 +9602,7 @@
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@@ -9608,7 +9617,7 @@
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-       "       <use xlink:href=\"#mdeacede841\" x=\"210.534559\" y=\"207.075738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"207.075738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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@@ -9679,7 +9688,7 @@
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+       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"391.479085\" y=\"353.211066\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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@@ -9692,7 +9701,7 @@
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        "     <g id=\"line2d_1\">\n",
        "      <defs>\n",
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+       "   <g clip-path=\"url(#p7753a0a83d)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
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        "   </g>\n",
        "   <g id=\"matplotlib.axis_3\">\n",
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_12\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m2457142bfc\" x=\"238.642398\" y=\"217.110852\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6f3befdbe6\" x=\"238.642398\" y=\"217.110852\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_15\">\n",
@@ -10511,7 +10505,7 @@
        "    <g id=\"xtick_7\">\n",
        "     <g id=\"line2d_13\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m2457142bfc\" x=\"271.107852\" y=\"217.110852\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6f3befdbe6\" x=\"271.107852\" y=\"217.110852\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_16\">\n",
@@ -10524,7 +10518,7 @@
        "    <g id=\"xtick_8\">\n",
        "     <g id=\"line2d_14\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m2457142bfc\" x=\"303.573307\" y=\"217.110852\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6f3befdbe6\" x=\"303.573307\" y=\"217.110852\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_17\">\n",
@@ -10538,7 +10532,7 @@
        "    <g id=\"xtick_9\">\n",
        "     <g id=\"line2d_15\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m2457142bfc\" x=\"336.038761\" y=\"217.110852\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6f3befdbe6\" x=\"336.038761\" y=\"217.110852\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_18\">\n",
@@ -10552,7 +10546,7 @@
        "    <g id=\"xtick_10\">\n",
        "     <g id=\"line2d_16\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m2457142bfc\" x=\"368.504216\" y=\"217.110852\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6f3befdbe6\" x=\"368.504216\" y=\"217.110852\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_19\">\n",
@@ -10574,7 +10568,7 @@
        "    <g id=\"ytick_7\">\n",
        "     <g id=\"line2d_17\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8cbd84fec4\" x=\"235.395852\" y=\"213.864307\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m290e0039d4\" x=\"235.395852\" y=\"213.864307\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_21\">\n",
@@ -10587,7 +10581,7 @@
        "    <g id=\"ytick_8\">\n",
        "     <g id=\"line2d_18\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8cbd84fec4\" x=\"235.395852\" y=\"181.398852\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m290e0039d4\" x=\"235.395852\" y=\"181.398852\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_22\">\n",
@@ -10600,7 +10594,7 @@
        "    <g id=\"ytick_9\">\n",
        "     <g id=\"line2d_19\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8cbd84fec4\" x=\"235.395852\" y=\"148.933398\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m290e0039d4\" x=\"235.395852\" y=\"148.933398\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_23\">\n",
@@ -10614,7 +10608,7 @@
        "    <g id=\"ytick_10\">\n",
        "     <g id=\"line2d_20\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8cbd84fec4\" x=\"235.395852\" y=\"116.467943\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m290e0039d4\" x=\"235.395852\" y=\"116.467943\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_24\">\n",
@@ -10628,7 +10622,7 @@
        "    <g id=\"ytick_11\">\n",
        "     <g id=\"line2d_21\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8cbd84fec4\" x=\"235.395852\" y=\"84.002489\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m290e0039d4\" x=\"235.395852\" y=\"84.002489\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_25\">\n",
@@ -10642,7 +10636,7 @@
        "    <g id=\"ytick_12\">\n",
        "     <g id=\"line2d_22\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#m8cbd84fec4\" x=\"235.395852\" y=\"51.537034\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m290e0039d4\" x=\"235.395852\" y=\"51.537034\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_26\">\n",
@@ -10733,10 +10727,10 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
-       "  <clipPath id=\"p685404ff3f\">\n",
+       "  <clipPath id=\"p7ad5c6487b\">\n",
        "   <rect x=\"40.603125\" y=\"22.318125\" width=\"162.327273\" height=\"194.792727\"/>\n",
        "  </clipPath>\n",
-       "  <clipPath id=\"p9d0a91b6a2\">\n",
+       "  <clipPath id=\"p7753a0a83d\">\n",
        "   <rect x=\"235.395852\" y=\"22.318125\" width=\"162.327273\" height=\"194.792727\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
@@ -10766,7 +10760,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 34,
    "id": "7e458c10",
    "metadata": {},
    "outputs": [
@@ -10781,7 +10775,7 @@
        "  <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2025-02-04T16:11:43.959018</dc:date>\n",
+       "    <dc:date>2025-02-06T12:33:35.955605</dc:date>\n",
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@@ -12107,14 +12097,6 @@
    "metadata": {},
    "outputs": [],
    "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4c5b4083-bf5c-4bc3-b98c-26fd07408d85",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {

From 5f6f3dc608bddef62cd94151cabd3365e513e5a5 Mon Sep 17 00:00:00 2001
From: AlessandraFumagalli <alessandrafumagalli95@gmail.com>
Date: Fri, 4 Apr 2025 13:35:38 +0200
Subject: [PATCH 12/14] Adapt model_profile.py to work with existing functions

---
 clmm/model_profile.py             |    42 +-
 examples/demo_model_profile.ipynb | 14716 ++++++++++++++++++++++++++++
 2 files changed, 14735 insertions(+), 23 deletions(-)
 create mode 100644 examples/demo_model_profile.ipynb

diff --git a/clmm/model_profile.py b/clmm/model_profile.py
index ebbf37047..3ffbfd50d 100644
--- a/clmm/model_profile.py
+++ b/clmm/model_profile.py
@@ -1,8 +1,7 @@
 import numpy as np
-import pyccl as ccl
-from pyccl import physical_constants as const
+from clmm.utils.constants import Constants as const
 from astropy import units as un
-
+from clmm.dataops import _compute_tangential_shear, _compute_cross_shear
 
 class profiles:
     '''
@@ -10,6 +9,8 @@ class profiles:
 
     Attributes
     ----------
+    cosmo : CLMM.Cosmology
+        CLMM Cosmology object 
     M: float
         mass (units: M_sun)
     c: float
@@ -27,13 +28,13 @@ def __init__(self,cosmo,M,c,z_l,z_s,compute_sigma=False):
 
         self.M = M  # M_sun
         self.c = c
-        self.a_l = 1./(1.+z_l)  # ccl works with scale factor instead of redshift
-        self.a_s = 1./(1.+z_s)
+        self.z_l = z_l
+        self.z_s = z_s
         self.compute_sigma = compute_sigma
         
         # physical constants with units (cosmological)
-        self.const_G = const.GNEWT * (un.Mpc/const.MPC_TO_METER)**3 /(un.M_sun/const.SOLAR_MASS) / un.s**2.  # Mpc^3/Msun/s^2
-        self.const_c = const.CLIGHT * (un.Mpc/const.MPC_TO_METER)/ un.s    # Mpc/s
+        self.const_G = const.GNEWT_SOLAR_MASS* (un.Mpc/const.PC_TO_METER/1e6)**3 /un.M_sun / un.s**2.  # Mpc^3/Msun/s^2
+        self.const_c = const.CLIGHT *  (un.Mpc/const.PC_TO_METER/1e6)/ un.s    # Mpc/s
 
         # cosmology
         self.cosmo = cosmo
@@ -84,14 +85,12 @@ def get_r_vals(self,nbins,lower_r,upper_r,log=False):
     
     def kappa_NFW(self,r_vals=None):
         '''
-        Create radial bins for profiles
+        Compute kappa or surface density profiles
         
         Attributes
         ----------
         r_vals: float or array
             radial bin values for halo lensing profile
-         cosmo : clmm.Cosmology object
-            CLMM Cosmology object 
             
         Returns
         ----------
@@ -104,7 +103,7 @@ def kappa_NFW(self,r_vals=None):
             r_vals = self.r_vals
 
 
-        Hz = self.cosmo.h_over_h0(self.a_l) * self.cosmo.cosmo.params.h * 100 * 1/(const.MPC_TO_METER*1e-3) / un.s   # units: 1/s
+        Hz = self.cosmo.get_E2(self.z_l)**0.5 * self.cosmo['H0'] * 1/(const.PC_TO_METER.value*1e3) / un.s   # units: 1/s
         r_200 = (((self.const_G * self.M)/(100. * Hz**2) )**(1./3.))   # units: Mpc
         r_s   = r_200 * self.c 
         delta_c = (200./3.) * ( self.c**3 / ( np.log(1+self.c) - ( self.c/(1+self.c) ) ) )
@@ -113,12 +112,12 @@ def kappa_NFW(self,r_vals=None):
         
         Sigma_crit_coeff = self.const_c**2 / (4. * np.pi * self.const_G)  # units: Msun/Mpc
         
-        D_s  = self.cosmo.angular_diameter_distance(self.a_s) *un.Mpc
-        D_d  = self.cosmo.angular_diameter_distance(self.a_l) *un.Mpc
-        D_ds = self.cosmo.angular_diameter_distance(self.a_l,self.a_s) *un.Mpc
+        D_s  = self.cosmo.eval_da(self.z_s) *un.Mpc
+        D_d  = self.cosmo.eval_da(self.z_l) *un.Mpc
+        D_ds = self.cosmo.eval_da_z1z2(self.z_l,self.z_s) *un.Mpc
         
         Sigma_crit = Sigma_crit_coeff * D_s / (D_d * D_ds)
-        critical_density = self.cosmo.rho_x(self.a_l, 'critical', is_comoving=False) * un.M_sun/un.Mpc**3 
+        critical_density = self.cosmo.get_rho_c(self.z_l) * un.M_sun/un.Mpc**3 
         k_s = critical_density * delta_c * r_s
         
         coeff = 2.*k_s / (x**2 - 1.)
@@ -234,24 +233,21 @@ def getTangential(e1, e2, center, dx=10./1000.):
         radius and angle maps, used for computing the radial profile
     '''    
     
-    n = e1.shape[0]
-
+    n  = e1.shape[0]
     xx = np.arange(-n/2, n/2)*dx
-
     XX, YY = np.meshgrid(xx, xx)
 
     center_1, center_2 = center
-
     from_cent_1 = XX - center_1
     from_cent_2 = YY - center_2
 
-    angle = -np.sign(from_cent_2)*np.arccos(from_cent_1/np.sqrt(from_cent_1**2+from_cent_2**2))
-    radius = np.sqrt(from_cent_1**2+from_cent_2**2)
+    angle  = -np.sign(from_cent_2) * np.arccos(from_cent_1/np.sqrt(from_cent_1**2 + from_cent_2**2))
+    radius = np.sqrt(from_cent_1**2 + from_cent_2**2)
 
     angle[np.isnan(angle)] = 0
 
-    et = - e1*np.cos(2*angle) - e2*np.sin(2*angle)
-    ex = + e1*np.sin(2*angle) - e2*np.cos(2*angle)
+    et = _compute_tangential_shear(e1, e2, angle)
+    ex = _compute_cross_shear(e1, e2, angle)
 
     return et, ex, radius, angle
 
diff --git a/examples/demo_model_profile.ipynb b/examples/demo_model_profile.ipynb
new file mode 100644
index 000000000..0740abaa2
--- /dev/null
+++ b/examples/demo_model_profile.ipynb
@@ -0,0 +1,14716 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "45308159",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "%config InlineBackend.figure_format = 'svg'\n",
+    "\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import sys\n",
+    "from astropy import units as un\n",
+    "import clmm\n",
+    "from clmm import Cosmology\n",
+    "from clmm.support import mock_data as mock\n",
+    "from clmm.galaxycluster import GalaxyCluster\n",
+    "\n",
+    "# profile modelling package\n",
+    "import clmm.model_profile as mod"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 151,
+   "id": "65ddbc40-cfa4-41b5-855d-4418b867f9c3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: function 'sqrt' is not known to astropy's Quantity. Will run it anyway, hoping it will treat ndarray subclasses correctly. Please raise an issue at https://github.com/astropy/astropy/issues. [astropy.units.quantity]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# r_2D = lensing_map.make_grid(npix,r_max)\n",
+    "c = 4\n",
+    "lensing_map.c = c\n",
+    "rbins = np.linspace(1e-3,50,npix)*un.Mpc\n",
+    "lensing_map.compute_sigma = False\n",
+    "kappa1 = lensing_map.kappa_NFW(r_vals=rbins)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 152,
+   "id": "7a41267c-0d79-40b8-b906-d9a7e7f3f2c2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "kappa2 = clmm.compute_convergence(rbins.value,Mass.value,c,z_l,z_s,cosmo,200,'nfw','mean')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 173,
+   "id": "f0554ee2-7c65-4385-a04e-773bbce666da",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
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+      ]
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+     "execution_count": 173,
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+    "plt.loglog(rbins,kappa1.value)\n",
+    "plt.loglog(rbins,kappa2)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 158,
+   "id": "e13b25c6-2783-4d6c-8294-05287caa8af7",
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+   "source": [
+    "lensing_map.compute_sigma = True\n",
+    "Sigma1 = lensing_map.kappa_NFW(r_vals=rbins)"
+   ]
+  },
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+   "id": "916b3198-cb1d-4d20-99af-1727f43647bd",
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+    "Sigma2 = clmm.compute_surface_density(rbins.value,Mass.value,c,z_l,cosmo,200,'nfw','mean')"
+   ]
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+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.loglog(rbins,Sigma1.value)\n",
+    "plt.loglog(rbins,Sigma2)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bd3eb025-713a-4b7e-90ec-148503994a6d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7ba07a0d",
+   "metadata": {},
+   "source": [
+    "Make sure we know which version we're using"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "bbd94d3a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.16.0'"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "clmm.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "66c330d7",
+   "metadata": {},
+   "source": [
+    "The modelling module can be used to create 2D lensing maps. This allows us to forward model systematics, starting at the map level. In this notebook, we use miscentering as an example systematic."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "909edd57",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# specify parameters for NFW halo\n",
+    "c    = 10   #concentration\n",
+    "z_l  = 0.5  #lens redshift\n",
+    "z_s  = 1.0  #source redshift\n",
+    "Mass = 1e14 * un.M_sun\n",
+    "\n",
+    "# define physical size of grid\n",
+    "r_min = 0 * un.Mpc\n",
+    "r_max = 50 * un.Mpc\n",
+    "\n",
+    "# number of pixels in grid\n",
+    "npix = 512\n",
+    "\n",
+    "# define physcial size of a pixel\n",
+    "dx = r_max/npix\n",
+    "\n",
+    "# define the center of the map (in Mpc)\n",
+    "center_1 = 0\n",
+    "center_2 = 0\n",
+    "\n",
+    "# define radial and angular bins\n",
+    "N_r_bins   = 30\n",
+    "N_phi_bins = 25\n",
+    "r_bins   = np.insert(np.logspace(-2, np.log10(r_max.value), N_r_bins), 0, r_min.value) * un.Mpc\n",
+    "phi_bins = np.linspace(-np.pi, np.pi+0.01, num=N_phi_bins+1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "de3d76d6",
+   "metadata": {},
+   "source": [
+    "Now we can create the convergence maps"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "id": "5b51bbc8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: function 'sqrt' is not known to astropy's Quantity. Will run it anyway, hoping it will treat ndarray subclasses correctly. Please raise an issue at https://github.com/astropy/astropy/issues. [astropy.units.quantity]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# set cosmology\n",
+    "cosmo = Cosmology(H0=70.0, Omega_dm0=0.25, Omega_b0=0.05, Omega_k0=0.0)\n",
+    "\n",
+    "# lensing_map has the option to return either Sigma map or the convergence map\n",
+    "lensing_map = mod.profiles(cosmo, Mass, c, z_l, z_s, compute_sigma=False) \n",
+    "\n",
+    "# make map\n",
+    "kappa_map = lensing_map.kappa_NFW_2D(npix,r_max) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "b0dc4b6c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+    "axlim = 2*r_max.value\n",
+    "plt.imshow(kappa_map.value,extent=[-axlim,axlim,-axlim,axlim],origin='lower')\n",
+    "plt.xlabel('x ({0})'.format(r_max.unit))\n",
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+  {
+   "cell_type": "markdown",
+   "id": "e073090a",
+   "metadata": {},
+   "source": [
+    "Repeat the procedure for a Sigma map"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "2aaf9cb0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# lensing_map has the option to return either Sigma map or the convergence map.\n",
+    "lensing_map = mod.profiles(cosmo, Mass, c, z_l, z_s, compute_sigma=True) \n",
+    "\n",
+    "# make map\n",
+    "Sigma_map = lensing_map.kappa_NFW_2D(npix,r_max)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "72993065",
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+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "axlim = 2*r_max.value\n",
+    "plt.imshow(Sigma_map.value,extent=[-axlim,axlim,-axlim,axlim],origin='lower')\n",
+    "plt.xlabel('x ({0})'.format(r_max.unit))\n",
+    "plt.ylabel('y ({0})'.format(r_max.unit))\n",
+    "plt.colorbar().set_label('$\\\\Sigma [M_\\odot\\; Mpc^{-2}]$',rotation=90)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4b28b017",
+   "metadata": {},
+   "source": [
+    "We can transform from the convergence to the shear with the Kaiser Squires algorithm, returning the e1 and e2 shear maps."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "eec34ea3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:201: RuntimeWarning: divide by zero encountered in divide\n",
+      "  oper_1  = - 1./(k[:, None]**2 + k[None, :]**2) * (k[:, None]**2 - k[None, :]**2)\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:201: RuntimeWarning: invalid value encountered in multiply\n",
+      "  oper_1  = - 1./(k[:, None]**2 + k[None, :]**2) * (k[:, None]**2 - k[None, :]**2)\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:202: RuntimeWarning: divide by zero encountered in divide\n",
+      "  oper_2  = - 2./(k[:, None]**2 + k[None, :]**2) * k[:, None]*k[None, :]\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:202: RuntimeWarning: invalid value encountered in multiply\n",
+      "  oper_2  = - 2./(k[:, None]**2 + k[None, :]**2) * k[:, None]*k[None, :]\n"
+     ]
+    }
+   ],
+   "source": [
+    "e1_map, e2_map = mod.KaiserSquires(kappa_map)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "25f42de1",
+   "metadata": {},
+   "source": [
+    "Plot the e1 and e2 maps"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "2ba6da86",
+   "metadata": {},
+   "outputs": [
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+     "metadata": {},
+     "output_type": "display_data"
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+   ],
+   "source": [
+    "plt.imshow(e1_map)\n",
+    "plt.colorbar()\n",
+    "plt.show()\n",
+    "\n",
+    "plt.imshow(e2_map)\n",
+    "plt.colorbar()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "12c04b61",
+   "metadata": {},
+   "source": [
+    "from the convergence map we can compute the convergence profile, and from the e1 and e2 maps we can compute the tangential shear profile."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f6af6b7e",
+   "metadata": {},
+   "source": [
+    "The getTangential function uses the e1 and e2 maps as an input, along with a map center, and returns e_tangential and e_cross maps about a given center. \n",
+    "\n",
+    "The function also returns a radius map and an angle map, which is used when computing radial profile with getRadial"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "6b8c1825",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:247: RuntimeWarning: invalid value encountered in divide\n",
+      "  angle = -np.sign(from_cent_2)*np.arccos(from_cent_1/np.sqrt(from_cent_1**2+from_cent_2**2))\n"
+     ]
+    }
+   ],
+   "source": [
+    "et_map, ex_map, radius_map, angle_map = mod.getTangential(e1_map, e2_map, [center_1, center_2], dx=dx.value)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "e743f1b8",
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+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.imshow(et_map)\n",
+    "plt.colorbar()\n",
+    "plt.show()\n",
+    "\n",
+    "plt.imshow(ex_map)\n",
+    "plt.colorbar()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cde1c95f",
+   "metadata": {},
+   "source": [
+    "With the radius_map and angle_map, we can calculate the radial convergence profile from the kappa map and the radial tangential shear profile from the e_tangential map, using the getRadial function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "e3d066a0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:298: RuntimeWarning: invalid value encountered in divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:299: RuntimeWarning: invalid value encountered in divide\n",
+      "  gammat_radial = _GT/_N\n"
+     ]
+    }
+   ],
+   "source": [
+    "kappa_radial, gammat_radial = mod.getRadial(radius_map,angle_map,\n",
+    "                                            r_bins.value,phi_bins,\n",
+    "                                            kappa_map,et_map)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f89da817",
+   "metadata": {},
+   "source": [
+    "plot the radial convergence and tangential shear profiles. Note that these profiles are not averaged over all angles yet, meaning that these profiles are 2D (radial and angular). This is useful for miscentering which leaves anisotropic signatures on the resulting lensing profiles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "080ff2f4",
+   "metadata": {},
+   "outputs": [
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+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.imshow(kappa_radial)\n",
+    "plt.show()\n",
+    "\n",
+    "plt.imshow(gammat_radial)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1086e4de",
+   "metadata": {},
+   "source": [
+    "We can recover the 1D radial convergence and tangential shear profiles as follows"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "5c6174be",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "kappa_1D_radial  = kappa_radial.mean(axis=-1)\n",
+    "gammat_1D_radial = gammat_radial.mean(axis=-1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ebb41586",
+   "metadata": {},
+   "source": [
+    "Plot the 1D radial profiles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "29a26710",
+   "metadata": {},
+   "outputs": [
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+       "<Figure size 640x480 with 1 Axes>"
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+    }
+   ],
+   "source": [
+    "r_bins_mid = 0.5 * (r_bins[1:] + r_bins[:-1])\n",
+    "plt.plot(r_bins_mid,kappa_1D_radial,label='$\\\\kappa(r)$')\n",
+    "plt.plot(r_bins_mid,gammat_1D_radial,label='$\\gamma_t(r)$')\n",
+    "plt.legend()\n",
+    "plt.xlabel('r [Mpc]')\n",
+    "plt.ylabel('Lensing amplitude')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "085bd120-6283-4d8f-adeb-bf4e2c781ba2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "81e0ceb4",
+   "metadata": {},
+   "source": [
+    "## Miscentering\n",
+    "\n",
+    "We now repeat the above procedure, but this time we use an incorrect center (relative to the true hale center) when performing the calculations, the exemplify the impact of miscentering"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "13660944",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
+      "  gammat_radial = _GT/_N\n"
+     ]
+    }
+   ],
+   "source": [
+    "# First we define a miscentring parameter\n",
+    "R_mis = 1 # Mpc\n",
+    "\n",
+    "# find new center based on R_mis\n",
+    "_phi_Rmis = 2*np.pi*np.random.random()  # isotropic angle for mis-centering\n",
+    "\n",
+    "# mis-centered coordinates\n",
+    "center_1 = R_mis*np.cos(_phi_Rmis)\n",
+    "center_2 = R_mis*np.sin(_phi_Rmis)\n",
+    "\n",
+    "# get tangential and radial profiles\n",
+    "et_map, ex_map, radius_map, angle_map = mod.getTangential(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
+    "kappa_radial, gammat_radial = mod.getRadial(radius_map,angle_map,\n",
+    "                                            r_bins.value,phi_bins,\n",
+    "                                            kappa_map,et_map)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "1cb19534",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map,ex_map,\n",
+    "                       kappa_radial,gammat_radial,r_bins):\n",
+    "    '''quickly plot the convergence, e1,e2, ex,et and radial profiles\n",
+    "    '''\n",
+    "    fig, ax = plt.subplots(2,3,figsize=[9,6])\n",
+    "    ax.ravel()\n",
+    "\n",
+    "    ax[0,0].imshow(kappa_map,origin = 'lower')\n",
+    "    ax[0,0].set_title(r'$\\kappa$')\n",
+    "\n",
+    "\n",
+    "    ax[0,1].imshow(e1_map,origin = 'lower')\n",
+    "    ax[0,1].set_title(r'$e_1$')\n",
+    "\n",
+    "\n",
+    "    ax[0,2].imshow(e2_map,origin = 'lower')\n",
+    "    ax[0,2].set_title(r'$e_2$')\n",
+    "\n",
+    "\n",
+    "    ax[1,0].imshow(et_map,origin = 'lower')\n",
+    "    ax[1,0].set_title(r'$e_t$')\n",
+    "\n",
+    "\n",
+    "    ax[1,1].imshow(ex_map,origin = 'lower')\n",
+    "    ax[1,1].set_title(r'$e_x$')\n",
+    "\n",
+    "\n",
+    "\n",
+    "    r_bins_mid = 0.5 * (r_bins[1:] + r_bins[:-1])\n",
+    "\n",
+    "    ax[1,2].plot(r_bins_mid, kappa_radial.mean(axis=-1), label=r'$\\kappa(r)$')\n",
+    "    ax[1,2].plot(r_bins_mid, gammat_radial.mean(axis=-1), label=r'$\\gamma_t(r)$')\n",
+    "\n",
+    "    plt.legend()\n",
+    "    plt.show()\n",
+    "\n",
+    "    fig,ax = plt.subplots(1,2)\n",
+    "\n",
+    "    ax[0].imshow(kappa_radial,origin='lower')\n",
+    "    ax[1].imshow(gammat_radial,origin='lower')\n",
+    "\n",
+    "    ax[0].set_ylabel('r')\n",
+    "    ax[0].set_xlabel('$\\phi$')\n",
+    "\n",
+    "    ax[1].set_ylabel('r')\n",
+    "    ax[1].set_xlabel('$\\phi$')\n",
+    "\n",
+    "    ax[0].set_title(r'$\\kappa$')\n",
+    "    ax[1].set_title(r'$\\gamma_t$')\n",
+    "\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e9720a7d",
+   "metadata": {},
+   "source": [
+    "we can plot all of the results at once using the plot_maps_and_profiles function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "32772d61",
+   "metadata": {},
+   "outputs": [
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PVtZZyJpO827nOFh0v9xOnuo8CjQ1wBwBFiFQNoEEYPvEBwe4BjaAaQuQqjpqIKoBKGQz7JNxDu/zJExEFkYp6yS/q2KKn+JetZiegqbLOP5XIwWPJWs79JjD8SbaCvDkv5mJBjRBk0bS0uMbAgzHoPcCirCOyFSrKjzKxBMCqRlhI92pASiyT1KdMdBy5MCDx9q0zTA5bQrQ6kelGFYJoImMw1dd13CQs4wDb8tUoxcNS4GQMQXn19DjLEDDsUwLMB12qU50AVDOBAlXb/hBNlHDjboiMFWAVI2whTazq14sE5ikwj4UPCGf9XdSZKWsYwNo0gPMgaQjs6R+jSryPVD8WIRfrSwW4u8sdk2jbeZirfL9JCxj6W/+58FhsonPmW75+FCgJeOWbaMy4TtAGQbJVoA06tbXcbaCqdFY1f7vgYnu9EDEAShvLwNQBIl1ipUBrC7BE/0dqpgyNpl01jdQe80tANZEy32d/EnDFTTrNsc01lKwoJy8GaOkbJOBhpSloNkKmBGwDIFkD0AG688xSLRH8Qn1675OyUYJiBrqOQBZerIVYR8OPJaYbJR1rN3wOPVqoimkgEn8HOXuEojBAevvHMBqpknFUhCQyS0BTW6acWZZLRyd5MXO7ADKCwKEE2U944id+i0dOcjkEwGJgIj1c5jm1IqJWCYBjwKUDoxkMwU+jUxGNzkrTIM1KEB9mtzPYQMEAUD+N5Szyr03ofZS+ZR5UoB0zTPGNEtYZhQwTB/bQYBGXk/2gosI10fRAmjsyyigANkB1PQ2AMUCiXRQkcoF0zDpCfuAgAeANR48RgHaQhkFq+1qFlLWIdhSHHqJaA+W5C+YhV5RvDfN9zq8XMQCiV9TiCUjEAEd+rqmK+P3jRA0CVNlA5kDyfeDCm+m1Q+DP7bB8kIZMQv796oJFW8CVazca7hTngMSShCxACLWThM8ASdxchCTLWMdt+86ZRnw0PvVKNto2Lqp5psy3r8JC6Lr3dHk2NkAQMk21EQTg0YCGHoB2wKUk4ABbAgsVGT8pesV2dOhLuh6pmAHSAFEbo7ZFSx+zlEAFWFl5dglmm3wbGPotoqoWp+qDGssPHiAOmg4U80A0BbRv8kjafFYfZq1KpppCdt4hlFGOaVkOwAlslALMCNgOYJliBw1+cUiNdWOApNURgcijbgJ9CfFPYgoCxEABXUJ+xjlfR3rzLYAGLvWdd46ImiC31RbyafgCACatUnMtSBGKRircDMaGqmPszC6AwEW/kxYRaVMQkFjOizTAExqnuUd4scgyIsDoSXCvshNtZGDOxFkgMBkbOQrUjAsw0DZONEcy2Ts4+tZo1LwwK53FWh/BfeRrujveJMuTmYigV0mZRIfR/t9wK/f+PCe9vaU8QGBZO0GHjDENEvC0cZvGwIWDjRGAJgeWJjxvys4Tmg7NdWOmvD3GiTG1wGy7gQUrD9u+lMAwc9/vZazdg0QKO0DAWaNaNmAjMBOyhJTiYkm+d8AmFkbaFjMeinYyFiLm5kwa+NYxzMNd7pCe8E8s2Y1z6hfIwINYSgWMPkvGTtWXhOzbBHS/7mWAeB05miKdJAFZlvuP1u6oUi+9faasm7Tm1+Bfazxv4FnvA8UUwLCnBPi/BygCiAVGcYmoJnjjHVyg8asF9zMlPhDyXARwKxm2urHwKrVr8lBE3wdhmUCYOQhZ/4cFLLl/L60NPoof6/aa5UNfUyAZIl5FwMFGYC8+ZbcomyV89YR/KbgFLi61q1QQmmsZhPXlxgQMBE0YR8AjNWYYXCDdmVQf3yBrtdY4/5iQMAggkYt7qIQggBrUABtwOT+DVCO/9Fz5pXOwaFw9EvJKfZwAAjZjyZbZBxfJrJQBiBgXRC1zs8JZ9bCv4ZW2RgosErBGr9IybBOXPCEM9VmZTDrBRMJEJjgy/i7O82ik7pAxjZWwZpgoiH+KW+yJaAJpllknwwwBDQF4+TbOOm8ITtvr0SKR6dfqpObB3nHySmWPLyuhHFImZVtAmqsYx0LQCMGCQLbWAqlEGQwClYDxriJbRjwRLbRCy4M42goBxqjksAB4IBiPGhcG2r1awJYjAIWBjSEZZRn0cJMo2POMU42lpulMe+6waAXkLwPBeMcCaRdV6CzKJrRSxkHyFknA5CFW9fx4FkrWP8vMA9W4BgLqzSMsbCTKboR/JbJg4djHGNUEaam89kYDWs0YZsKaBYSCCDrOKVfAx4oL3heXOPtameBqjd3u6bai4QRD2pjS1/j4ObObsE667ay2TqO+yAkIvMs8OEDwC2grqxjjMZiVuef3p82K+MZJw1Ha2gYZXBV5QLp4nUmbLMEsChgQQqaAJjIOIoFDGuaHTXWQ5W4xmVVz5y79/FxDjig5qAM6E/0MJG3mK+yP6u82WbJpX+dhPHxg0XBag2rF1ij4gQ3/g9woLnoBdr7OBe1JMC52glXq3HRC57NFNOD2WdMCAYAdtEOOAYONDcHILV4oCzELCOskwCnNj5bzxv1JTM5BEx38IHk38fZI2cC5cArIioggsdDYrp5v8DqABYLTGVlqwAsgNUaRgPGGCxWYTE69XVgcVEGF5UBx+u6qQk30kHrdQQzzhjtQHPzJtpNpaAxATRtwOTg2XvVri5IV8D06oHk25rzhN2NH0iPI2AZclgFfVQZcALJRMbx6evk83cITN7nIKus1kfYjFYwWntzLWUdAJFtHvUNkw8OLFYDBngiazuh3mIUlkXDLBpmUbAMaHQw1RYSFKDAwQoWSeSMH6x6ehUYlYsULb/ZR9lh3ol0YfQJ0BeQXWDp7bf00/LMVTKEo+H9nAiiyDzwi54ArIW2PuIVfCVoWA0s2uJ207hMni2IuTbB4OLBc9E3AMDVzDBa4WJS880xjcayuD9708BNQ10V1FVB39QKmCSihoRlmoGAfAxrk88KJ7mqAONMEEUFO+tn8mrWcaSA6TJLr/yovlAO5OQR5okgCgAyayTN2PA2GiCu62iNRU+4zsabWjr1ddSCN/qKi3K3b07a+jA0BY3GYjSuy4TlNjnQXD3LBNDcAH1LQRP6yEbQamNRGZd8IufzujDR6H5mphXra4xCtuwd5e7A2cwwDUC0wFLVITHfyEZgn3g7jnb7ZgoA8qFr/2yOsQCUYx0zGdxuGs+3CbdLCRxnrl1dWwZFsOBmfN2bN9GuGuqmoZ4V9FU5wNz87+KOTfvfnHGkx54PQr4mZrMyBVvU2Fx9mgC6K3DEV/sWawhAwaZLwFTpI2WewEQBPDqs8Fu37QDkwRN9nQm3yeK6THheJtzsBGOVM9U8aN6oZ9eGBj5ad5qMVbhZV+e6TLjdJpjnybHNk4J+dmDRV8c4ynjAZH5N7suIol3ErEpMLJVmF0OYAyMHBNUxCKB7gucuwNlslkmYRAiYZvkOExVzypttNjCPdld6OwHGr9QrE+4r0DAKWPSE52nGx3nG02XG9UFj8fejvVHPeKc9cAzwQT0AAK5W4+k24+N1xvPzjOVpAp419EeN6VlBP6+g0WT9JgIn82dakgdHKGCSdS5mcGpAURXQiU24V8Q+Lw6cQ0AzwjIdwNTLWb5cReK9bNptWO3+1OzBsygSAnbguU4WT5cLvr1d8GxmzzoWb/QVbzxwrnbCBPfw2rOZ8e3tgqfrBdenGXiaoL/VmJ4UpicPHG+eBcZZfRsrPg5XMOyrOGk5wHD+fcjggCJln9DXHnjYci8gLwacw6JlHdB0WaYBGBYsHYDFvsT/bAIce1PQE2Au4ervJyI0jJrwcb7g/eWCD7cHXK1bCHpQC955U+2q3Sm62gkfbg94/3zBx48X2G8n6A8a00fl/p4BfXV/jmlsEXZuhmmZX7deZQnjqKJa4roEMJDfAiiEVars0wMP0jKhXGznBeRFgPPioBlhGcowGWDycl22ip3Deq+ato55bspN6hDpMm5Rc9HAh8sjvnnziPe3RyxQuKgb3uonAMB7+4AFCu9vj/jm+RHvv33E8v4C/X7C/EFh+lZhegKmZ/hImmXDznn/AI5dVrMzTmBF56p75pXqiRPbCtnnCPAwZZplT5DTgTOy8nwoaPKyDIvkLMOuoJN0ldQr6+d9W8Hj7m0zc2AFBe3Bc7UTPk6P+OrhM/zqszd4MhdnroVwNCyezAW/fP4MX334DE+/foT+ZsLlG435W2D6FpierdMbzTOb9hdgTbBkPSrkkbQ4z/0kdT/WH27KPvkd5pyJdTh4KvIS4DkVOKLFxj0i1T8AGnZBMMtPJiYLrBy9iIEDMytMF4vlGdDPbnX/GTO+vnyGn775AX7x7h0WKLxTbgF0gcIvbu/wTx++j6+//gz6qxkPX2lcfg3M31pMTx6MgWks176bRZYAQ6n1IT2r1eqjYf2Nx6+ydG/CWYKuwlQDislfnJ+9k7uh42zwnAacUdBsYps8rWZK5fWybQ40LCgC2CySKJUylgUW4E2mcJXWfpJOwHJRjjGeFPRV4yMe8dPL9/GT7/0Q79894tGf9PfmET/58EP89JffB372iDf/T+PhV8DlvcX0ZDFdbeLTxMMKjzwEfyuARMG/8X3NU+4zbzGN/sVIGkrwxLFk2KNglxobZfWOMtmq5Q+Suy+AbpYOY/VCyxEAPebLQEN9B7e9+hTK2rjgGCey9aDy4AoT12oFc1G4vFeYP2joq8YH9RZ/9+538fef/w6mN/8AAPj759/B3/3id7H841u8/UeNNz+3ePi1wfzRQl+tm/S5bgW4xxkcUJXy99Ap5R+B8EAJH9tRAHR4Z08GjMrYBrMtBgyYCd+duEewzp3kFOC8Brap6qcmWpKGjk9jk/wCNMZm0SwLtVi/bwG/Tdu3SuFhUnh8M+Hx6xmXX2t8hS/x15//CP/++/8DAPDXv/gRvvpfX+Lz/6Xw9p8WPPzqhunj4nQTPcGXwhSe/1Gwk4rRPVgFTOtMtf5VvtB+yCxW519RcBCzDSWoEpMNHVaQsg5Xt1XuDqzz6TLOXukxjS+TBwRWgK0+hYrbwYzzoIl/xqXdDNTNADcDZQywGMBaXJTC409nvP0/j3jzi8/wt/ZH+O9/8M8BAH/7Nz/CH/xX4N1PPmD65gnqekN8zeikYbUGZg0b/oxLXx9xcMBS1vo3jvqZZAELt6388QVQKFsCpDqGZzDGJ8BE323gVJgrSCtMnvpHacHCX8rZijBLYJwAGnVdgNviAHC9Abcb7PUKdbthNhZf/N2Mz//n7+Gv8JdQFviz//xL4Kc/c2W1AuYZ6nIB5hm4+D9LUDJr1wkN97yPsVCavgaX/DFXf2VX86sFoO6V/xOY/Hsk/27Rb+W1SHTqv8Oz7xOW7zbjsAb6KuFJTq6exZoXTZ28XiUKpcLLCIMDbpVjgiCTN6cuczS77GXG8oNH/PpPPsP//bfAf/h3/wUA8Ff2L/H7/+0LfO8n32L62plqlppqswY0MdWCfxOiZDFYwPyhZA0K1GSNB3k5ftzY7e+gfLeB0xIGSFyZCCBFfADATfawgKGUezmh9REsrRId0Bp2sVCTBi6pU28nheXNhOfPZ7z//Qlf/0uDP/9XP8a/eXRRtT//1z/G36of4eOXb/H2n97UgwMBIEVwwAcOQpRNKf9Equ+337Y5mCQT/yxwfAKgOwU41Ss5ILvyV5iC05tc/fMwEKdfwYVdsy/ocuZ5Chr/3poAII31A1NBibL+5Rw+6japdY3HkPZIOPr2mcbz9xQ+/o7Chz8y+OJPf4G/+PLHeOM78xdf/hj/+09/iK/wJa7fm/Dm5xoPv7aYvzVJODrRHSJs9Hci4NFADFcnbKkK8KT5KCY1rRPr5aLSX65MNfJVtNcvI9K7Uz5dxukwRgGorI5V8TsD7fC5okAKzIL1u+nkRi1r3StvlVk/aKvMeubyBdDlUeH6TuH5c+Dj7xrMf/QBf/blz/DHDz+Pn+/444ef48++/Bn+5g/f4APewlw0br9y6z/yBVCVAGFloQCiFQAStll1ZcyabXcn7SfALDU5DTivgXVo2Zx1qO68aihfRKGsy1DG+rWRUEmlH+HNjzuYR/6WG3MBlkfg9lbh+j3g+QsD/LMn/OEPv8afvP0l3uknPHkd7/QT/uTtL/H3P/wC/3Cd8BGPMBeN5ZHeedC/5Ybeq5azSQ6sAkC1dKTbltseZZvadqXuPdgGOJlxRsEzLC0dDPDC/VgBIdFky8AD0u8Cj/5Kq6z36+36bR0g1HNnLL3JEzCze7xgeVBYPgNuby2u37cwX1zxxQ++xe+9/QZfzu8xweK9f+pzgsWX83v83ttv8M0PHvHVdcIzZthJwTwocpOnIjd5uv70bvLMgVA1zwCmLDHRFAMUuj044cVyJ9AAL2CqNcHTKythnZxdMjDl6Val402/0EZBE9lHIV0DgdeDUE4xDENBszKNnYHlwbHN8pnF7Z2F+f4Nb773jC/efovPLx/xqK9YoPDRr80sUHjUV/zw4Vt88fZbfHy+4KMBrnb27y9QME8qe6yg/HRH3r8wNsV+DUjxuNRap6WHEQ5cu9imImeDBnghH6cV9j3EZOPAQ3WSYmE/Lxed/1CemmoETDl4iuPxv/FBNq1gZsBGtgGWNxbLZxbm7YLp7Q1v3zzh+w9PeDc/YYLF1c74YB4BOIBMsHg3uzJfv3nC9TphWRRuanJtTA6U+gqY8JKOjQ+yFQyT5Cm+fAVALECOAk0PnCfLiwUH6F2zidDZTMruAU9sJ7GxUmDlYHL6VpvNraCjPemY40senZ7cn/GL++YBWB4tljcW5jMD/faGN2+uePdwxdv5Ob4S6tlOeG/dewY+mgsA96abt/Mz3j1c8fTmig+38HYc95lDeHNQzYBlXwtl13ERHEcCFjpQPZZpsc8RoLkzYIK8eFRNyj5d8AB1oABD7BMSUpNOJQWa842YNOFlHQE4ZgpsYyNwzBsDPC6YHxY8Xq74bL7iQd/8JwoVPvqH2QAHogXuvWoP+obP5iseL1dcHyc8L/61Ux48VruH5KzmXtax+mUi35KZzNxkF7FMR0dt/7WCBrhTOLrJPoxDq2qzvQUUDlS0D6RNGnnL77HiQF7zDeIaifaA0QQ0M2AeLcyjAR4MpscFDw83vLnc8DjfcFEGEwyM1fhoH+IXoj/a9V0EF2XwOLs6zw839xZPs4LHwq0raa0c60wnvB4qzxswwY42ze4BmCB3Xcdh2adiugEVAAmAkhNX3MgBkxQo6xZKVAmauC4STLTZg+bBwj5Y4GKhHxbM84LLtOBhWjD7Fw4u0LjaCU/mEu8ifDIXGLt+hW1Wrs5lWnCdF9iH8AUE698Y6gZVaefrGH9sioBn/SK2P0Zh8KYYHwkoWnmfgC9Tk7svgI76PknZDoBi2QqIKNvUThDXVwqYxEQjvo2Z/cNjnnHsxcLOBupiMM0Gl8uCh3lxX5v2nVg/6TFFxgn79G2fszZ4mBc8zwbLzcJejPvmqNURPO7WH8R3SIe+hbWeYLJRAEmjn8lYkLEU53/CgAlyd+AEORxAfj8f6HzcbVaeLYQUNAnT5IwzAXaya2DgYmFn94eLhZoN9GQwa4NJG0yqBM5Hc8Hi73e7mrkAzqRc3cu04Dbr9fs4/nkgd1ODApT7opvSJFCgMsYhfzHaWBx8fVzYcayV/Q4AJggPnD2dHKF9rnrNv2AmeItZmvprfeyYFOy6BvFrrCaAmRABYy8WmA3UbDBNBvNsoLVxnywkoFmgcTUTtH/ROuA+83E1JetMykJrp8ssBnb2H5byNp4BoJSCVn5wFAD/8akQMEjA4sGUhNzDdm9ca/lSv+QlwHLwnF6Bc1QnOT0bwbQVRLH8wAlttV2AhZpp0bfxoAmsM1vHPLMFJgs1W+jJQk8eNLr8LOHNTLgqZ6blLBT8HACx3qQdePRkoI125qG1yYKtgXvCUym4O6rpSzlqjEPGesR8644jlTPBcjQ7MfNtPryRXsOk8RFhgcHp9vo3nYCas+vzOMDA+xLu7mMGNNoDxwNGa8cWkzZQZFYaKFytxuwjaPHjuXb9lKEhHVReh2MeByA7IX6m3c5rv+OBKQCL9f1XSbAgYRzOfM23R2TExDtY/+Hi27qPj3MCkIAxR7+lh+rIgwArcPwCaQIaG30cTC4vgEZpQGk3yZVK2cZYhauZMCuDm5lgVPo9HGM1jDfZqLmmldelLZS2ro3JwBr/vMCEcCORB41nmwXuUYRARYy/Q+/Vy8ckGesBOcz0egX+Thc4ew5WPLgHmXe7TkzONjXTzIMmsA50BhoNN2EnxzSY/KQmzDBpwjS+0+4THhraakxQ0D5GbOC+vnbzH6DKP38YzTWtfSDAt+1vPlVQJNxsHXgmfzwGsMoWi6NxG0hAFPZ3j/WI7GjnzLlbAOfIAWnp6oKqVnenzd2NmJHfkm1sGnYOjKMpaKwDlv+LTKCdqZY3BXhWCQAxE4yy0P7hGuMBs/gy3KEowOnWCspOUNrGz8lbC6gJWF9ZaxG/r6i8qaZ8KM6WAApRuFA1CeEng1gdcZlsnHdnAbjqGniZ7xXm2wyqI69Aqtzm2YaYZeEX4EEzraCJwAnmlEI0r4Ksppgz06DdowQ6MBEFVCyb+jpOJ6C1hTWedcIDdzbO9wQ8Ci7ChgnrSwnDG0gpgFzx4g7zkE7Hb28goSavIRSd9+HVrONQOWWgGqDJ12hiWgAMCQikazcENOEq74EF79Mo7Sa3UuGXMdPgPk8Y3qzJMc7NatzMGiDIwZO0oZVjHbv6L1bb9TEId4TRjFPaMxMC26QAiqyTM44HUjKOJ4HntUkbOPdE+h7/qFOuda8VC5j8NwJl3Q5ggXaXZ+XZxq2hpIBJDjP4LdAw1uIGDZ0xzurbOBDZypVFKdKehvNzwiPe8CAC+VSH8mZbeOTaP9W6mmsEQGGMbAaQrUxz9Pk9Qxp9TIHzCigxypa+VOpUTTSV5VcAE+dcNNVWXyeAxkaQuHJhWwEs2wAeNAEYypljs3aPFlB/xgRTLZRFCZ6EdbBeAOIn5L1/psjsd/v+ndEWbnGUsAsHoAgUAp488lYFUmbavXrJ+0j6f846zh0HpbsynTOPP8u1W2oKxtE0QOCjawEwPl/59BpggPUcBDa5GY1ZOz9HZ7fhGL+GczM6iapx83MFkP90hw4Loir2VSkV3x0dwWNUYrIF/Yk7o1JzLw5lbrJx/aLKXlqOMh9J/+U+ziu6QnR9IJE/IwBMnp6DRq+/7uoeAGRTsymAKOuWsQrKKizWOTfGBrrQyRufqLm22BQ89BBDO7RdGzJCsEBHjnG/hgDMqAQDOfuEQEMEUKS2zvSw7XN2VlBhbWCgrLAvx9+rtkGOWn+ppaU+TQMwdJ9u03Ubsk+DCQimG2GfMGc5MVZhIqyiPaPkt+GE/ODbUMDk4ImHmJhroU/K9XFB0ner1whbYKfwSqvwwlBgHY8EQHBs5fLXvohOZx5UGJBTgcb1hWnvMFPt1JDhKMNAABby22QZVQGNpturf7OaZ4gmWi0wYKyCtgrum7oK2q5+el6O+kM5gJKh8DZRMNcCaFafB+5mTw8YGAIeC7euE95KGnwceABZYr6F/UBRnoWADEScidYz2zrAOHNhk69UJg2Fo08Dx6jeHlCAZIS6gPFpXdCE8pr6NZR9SICgARrrJ79V1rMNopmmLbBYFeuFIEAOGkv0FMOjwjdrPGXEPinSNxX9nTAW3kqMX5ELH5py/SDs48HC4cENIRn7rFQVSEmh4pDa5QfkKJORBc6hADnaDPPCBwEYsFA9KssjwBGBJg8GxDor24R0lfWHE2PXiakIQHR0INZy4Ze77YYVZaE8wELf1uNS8aq/fmCK+DgC8MQxQ3ma0uBZapPl3W4GDWrDJ5lTG8BVG1LuNM6tCmJ5gfrVPuYhXilg/K/N96tMk/k1FbYJZhp7DIBnDDepJ+XuJwsmG2UaKnTtJrBN2DbWM09teHzfVnM0ZZ10PMjnDGvg8f9JAESDAsqG/0Keoj9rf1PU8SIBxQ5TsCjO9HHslpsXBJgUKEVZZrtqqoVtRcu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+       "   </g>\n",
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+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map,ex_map,\n",
+    "                       kappa_radial,gammat_radial,r_bins)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "510b4c9c",
+   "metadata": {},
+   "source": [
+    "We can also investigate how the 1D radial lensing profiles change as a function of miscentering"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "53fa70dd",
+   "metadata": {},
+   "source": [
+    "Now define a miscentering distribution"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "38b199f1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# define miscentring distribution\n",
+    "R_mis_max = 1 \n",
+    "N_R_mis   = 15\n",
+    "R_mis_arr = np.insert(np.logspace(-2, np.log10(R_mis_max), N_R_mis-1), 0, 0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "c17883c2",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:248: RuntimeWarning: invalid value encountered in divide\n",
+      "  angle = -np.sign(from_cent_2)*np.arccos(from_cent_1/np.sqrt(from_cent_1**2+from_cent_2**2))\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
+      "  gammat_radial = _GT/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
+      "  gammat_radial = _GT/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
+      "  gammat_radial = _GT/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
+      "  gammat_radial = _GT/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
+      "  gammat_radial = _GT/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
+      "  gammat_radial = _GT/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
+      "  gammat_radial = _GT/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
+      "  gammat_radial = _GT/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
+      "  gammat_radial = _GT/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
+      "  gammat_radial = _GT/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
+      "  gammat_radial = _GT/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
+      "  gammat_radial = _GT/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
+      "  gammat_radial = _GT/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
+      "  gammat_radial = _GT/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
+      "  kappa_radial = _K/_N\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
+      "  gammat_radial = _GT/_N\n"
+     ]
+    }
+   ],
+   "source": [
+    "et_map = np.zeros((N_R_mis,kappa_map.shape[0],kappa_map.shape[1]))\n",
+    "ex_map = np.zeros(et_map.shape)\n",
+    "radius_map = np.zeros(et_map.shape)\n",
+    "angle_map  = np.zeros(et_map.shape)\n",
+    "\n",
+    "kappa_radial  = np.zeros((N_R_mis,N_r_bins,N_phi_bins))\n",
+    "gammat_radial = np.zeros(kappa_radial.shape)\n",
+    "\n",
+    "for j in range(len(R_mis_arr)):\n",
+    "\n",
+    "    _phi_Rmis = 2*np.pi*np.random.random()  # isotropic angle for mis-centering\n",
+    "\n",
+    "    # mis-centered coordinates\n",
+    "    center_1 = R_mis_arr[j]*np.cos(_phi_Rmis)\n",
+    "    center_2 = R_mis_arr[j]*np.sin(_phi_Rmis)\n",
+    "\n",
+    "    et_map[j], ex_map[j], radius_map[j], angle_map[j] = mod.getTangential(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
+    "\n",
+    "    kappa_radial[j], gammat_radial[j] = mod.getRadial(radius_map[j],angle_map[j],\n",
+    "                                                      r_bins.value,phi_bins,\n",
+    "                                                      kappa_map,et_map[j])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "22ba0469",
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+       "   </g>\n",
+       "   <g id=\"matplotlib.axis_7\">\n",
+       "    <g id=\"xtick_10\">\n",
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+       "      <g>\n",
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+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "R_mis_ind = 10\n",
+    "plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map[R_mis_ind],ex_map[R_mis_ind],\n",
+    "                       kappa_radial[R_mis_ind],gammat_radial[R_mis_ind],r_bins)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2dbde4d3",
+   "metadata": {},
+   "source": [
+    "Finally we can plot the lensing profiles for the whole miscentering distrubtion"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "7e458c10",
+   "metadata": {},
+   "outputs": [
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+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for i in range(N_R_mis):\n",
+    "    plt.plot(r_bins_mid,gammat_radial[i].mean(axis=-1))\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ea9ce0dc",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
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+   "pygments_lexer": "ipython3",
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+}

From d1c664415530dfa7d5c135669fe47e7702ff14fc Mon Sep 17 00:00:00 2001
From: AlessandraFumagalli <alessandrafumagalli95@gmail.com>
Date: Fri, 4 Jul 2025 11:16:46 +0200
Subject: [PATCH 13/14] Updated model_profile by replacing function with
 existing ones in clmm Updated example notebook

---
 clmm/model_profile.py             |    93 +-
 clmm/modelling.py                 |   245 -
 examples/demo_model_profile.ipynb | 20599 ++++++++++++++++------------
 examples/demo_modelling.ipynb     | 12123 ----------------
 4 files changed, 11777 insertions(+), 21283 deletions(-)
 delete mode 100644 clmm/modelling.py
 delete mode 100644 examples/demo_modelling.ipynb

diff --git a/clmm/model_profile.py b/clmm/model_profile.py
index 3ffbfd50d..0e4cfb10e 100644
--- a/clmm/model_profile.py
+++ b/clmm/model_profile.py
@@ -2,6 +2,7 @@
 from clmm.utils.constants import Constants as const
 from astropy import units as un
 from clmm.dataops import _compute_tangential_shear, _compute_cross_shear
+import clmm
 
 class profiles:
     '''
@@ -9,31 +10,47 @@ class profiles:
 
     Attributes
     ----------
-    cosmo : CLMM.Cosmology
-        CLMM Cosmology object 
-    M: float
-        mass (units: M_sun)
-    c: float
-        concentration
+
+    cosmo : clmm.cosmology.Cosmology object
+        CLMM Cosmology object
+    mdelta : float
+        Galaxy cluster mass in :math:`M_\odot`.
+    cdelta : float
+        Galaxy cluster concentration
     z_l: float
-        lens redshift
+        Redshift of the lens
     z_s: float
-        source redshift
+        Redshift of the source
+    halo_profile_model : str, optional
+        Profile model parameterization (letter case independent):
+            * 'nfw' (default)
+            * 'einasto' - not in cluster_toolkit
+            * 'hernquist' - not in cluster_toolkit
+    delta_mdef : int, optional
+        Mass overdensity definition; defaults to 200.
+    massdef : str, optional
+        Profile mass definition, with the following supported options (letter case independent):
+            * 'mean' (default)
+            * 'critical'
+            * 'virial'
     compute_sigma: bool
         True for computing Sigma (surface density) profiles,
         False for computing kappa (convergence) profiles
     '''     
     
-    def __init__(self,cosmo,M,c,z_l,z_s,compute_sigma=False):
+    def __init__(self,cosmo,mdelta,cdelta,z_l,z_s,halo_profile_model='nfw',delta_mdef=200,massdef='mean',compute_sigma=False):
 
-        self.M = M  # M_sun
-        self.c = c
+        self.mdelta = mdelta  # M_sun
+        self.cdelta = cdelta
         self.z_l = z_l
         self.z_s = z_s
+        self.halo_profile_model = halo_profile_model
+        self.delta_mdef = delta_mdef
+        self.massdef = massdef
         self.compute_sigma = compute_sigma
         
         # physical constants with units (cosmological)
-        self.const_G = const.GNEWT_SOLAR_MASS* (un.Mpc/const.PC_TO_METER/1e6)**3 /un.M_sun / un.s**2.  # Mpc^3/Msun/s^2
+        self.const_G = const.GNEWT_SOLAR_MASS* (un.Mpc/const.PC_TO_METER/1e6)**3 /un.M_sun / un.s**2  # Mpc^3/Msun/s^2
         self.const_c = const.CLIGHT *  (un.Mpc/const.PC_TO_METER/1e6)/ un.s    # Mpc/s
 
         # cosmology
@@ -83,7 +100,7 @@ def get_r_vals(self,nbins,lower_r,upper_r,log=False):
         self.r_vals = r_vals
         return self.r_vals
     
-    def kappa_NFW(self,r_vals=None):
+    def kappa_or_profile(self,r_vals=None):
         '''
         Compute kappa or surface density profiles
         
@@ -102,33 +119,16 @@ def kappa_NFW(self,r_vals=None):
         if np.all(r_vals.value) == None:
             r_vals = self.r_vals
 
-
-        Hz = self.cosmo.get_E2(self.z_l)**0.5 * self.cosmo['H0'] * 1/(const.PC_TO_METER.value*1e3) / un.s   # units: 1/s
-        r_200 = (((self.const_G * self.M)/(100. * Hz**2) )**(1./3.))   # units: Mpc
-        r_s   = r_200 * self.c 
-        delta_c = (200./3.) * ( self.c**3 / ( np.log(1+self.c) - ( self.c/(1+self.c) ) ) )
-        
-        x = r_vals/r_s
-        
-        Sigma_crit_coeff = self.const_c**2 / (4. * np.pi * self.const_G)  # units: Msun/Mpc
-        
-        D_s  = self.cosmo.eval_da(self.z_s) *un.Mpc
-        D_d  = self.cosmo.eval_da(self.z_l) *un.Mpc
-        D_ds = self.cosmo.eval_da_z1z2(self.z_l,self.z_s) *un.Mpc
-        
-        Sigma_crit = Sigma_crit_coeff * D_s / (D_d * D_ds)
-        critical_density = self.cosmo.get_rho_c(self.z_l) * un.M_sun/un.Mpc**3 
-        k_s = critical_density * delta_c * r_s
-        
-        coeff = 2.*k_s / (x**2 - 1.)
-        f_internal = 1. - (2./np.lib.scimath.sqrt(1.-x**2)) * np.arctanh(np.lib.scimath.sqrt((1.-x)/(1.+x)))
-    
-        nfw = coeff * f_internal.real
-
         if self.compute_sigma:
-            return nfw   # units: Msun/Mpc^2
+            return clmm.compute_surface_density(r_vals.value,self.mdelta.value,self.cdelta,
+                                                self.z_l,self.cosmo,self.delta_mdef,
+                                                self.halo_profile_model,self.massdef) * un.M_sun/un.Mpc**2 
         else:
-            return nfw / Sigma_crit # units: adimensional
+            return clmm.compute_convergence(r_vals.value,self.mdelta.value,self.cdelta,
+                                            self.z_l,self.z_s,self.cosmo,self.delta_mdef,
+                                            self.halo_profile_model,self.massdef) * un.dimensionless_unscaled
+
+            
             
     def make_grid(self,npix,r_max):
         '''
@@ -150,10 +150,10 @@ def make_grid(self,npix,r_max):
         npix *= 1j #imaginary so that ogrid knows to interpret npix as array size
         y,x = np.ogrid[-r_max:r_max:npix,-r_max:r_max:npix]
         r_2D = np.hypot(y,x)
-        
+
         return r_2D
 
-    def kappa_NFW_2D(self,npix,r_max):
+    def kappa_or_profile_2D(self,npix,r_max):
         '''
         Create 2D NFW profile on a grid
         
@@ -166,16 +166,17 @@ def kappa_NFW_2D(self,npix,r_max):
 
         Returns
         ---------
-        kappa_nfw: array
+        kappa_or_profile: array
             NFW profile (Sigma or kappa) for each point of the 2D grid
         
         '''
         
         self.npix  = npix
-        self.r_max = r_max
+        self.r_max = r_max 
         r_2D = self.make_grid(self.npix,self.r_max)
-        
-        return self.kappa_NFW(r_2D)
+
+        kappa = np.array([self.kappa_or_profile(r_2D[i]) for i in range(self.npix)])
+        return kappa
 
 
 
@@ -212,7 +213,7 @@ def KaiserSquires(Sigma):
 
     return e1, e2
 
-def getTangential(e1, e2, center, dx=10./1000.):
+def get_Tangential_and_Cross(e1, e2, center, dx=10./1000.):
     '''
     Compute tangential shear profiles
     
@@ -251,7 +252,7 @@ def getTangential(e1, e2, center, dx=10./1000.):
 
     return et, ex, radius, angle
 
-def getRadial(radius_map,angle_map,r_bins,phi_bins,kappa_map,et_map):
+def get_Radial(radius_map,angle_map,r_bins,phi_bins,kappa_map,et_map):
     '''
      Calculate the radial convergence profile from the kappa map 
      and the radial tangential shear profile from the e_tangential map
diff --git a/clmm/modelling.py b/clmm/modelling.py
deleted file mode 100644
index a257f6c47..000000000
--- a/clmm/modelling.py
+++ /dev/null
@@ -1,245 +0,0 @@
-from astropy.cosmology import LambdaCDM
-from astropy import constants as const
-from astropy import units as u
-import numpy as np
-import matplotlib.pyplot as plt
-
-class profiles:
-    
-    def __init__(self,M,c,z_l,z_s,sig=False):
-        import numpy as np
-        from astropy.cosmology import FlatLambdaCDM
-        from astropy import constants as const
-        from astropy import units as u
-        
-        self.M = M
-        self.c = c
-        self.z_l = z_l
-        self.z_s = z_s
-        self.sig = sig
-        
-        self.cosmology()
-        
-        return
-    
-    def cosmology(self, H_0 = 70., Omega_m = 0.3, Omega_Lambda = 0.7, Tcmb0=2.725):
-        
-        self.H_0 = H_0
-        self.Omega_m = Omega_m
-        self.Tcmb0 = Tcmb0
-        self.Omega_Lambda = Omega_Lambda
-        
-        return
-        
-        
-    def get_r_vals(self,nbins,lower_r,upper_r,log=False):
-        '''create radial bins for profiles
-        nbins: number of bins
-        lower_r: lowest bin value
-        upper_r: highest bin value
-        returns bin edges in units provided, or kpc if none are provided
-        '''
-        #create r values
-        self.nbins = nbins
-        self.lower_r = lower_r
-        self.upper_r = upper_r
-        self.log_r_vals = log
-        
-        
-        if self.log_r_vals:
-            if self.lower_r == 0:
-                raise ValueError('log(lower_r) cannot be evaluated for lower_r = 0')
-                
-            r_vals = np.logspace(np.log10(self.lower_r),np.log10(self.upper_r),self.nbins+1)
-            
-        if not self.log_r_vals:
-            r_vals = np.linspace(self.lower_r,self.upper_r,self.nbins+1)
-        
-        #if no units are provided, set units to kpc, otherwise keep input units
-        r_vals *= u.dimensionless_unscaled
-        if r_vals.unit == u.dimensionless_unscaled:
-            r_vals *= u.kpc
-            
-        self.r_vals = r_vals
-        return self.r_vals
-    
-    def kappa_NFW(self,r_vals=None):
-        '''r_vals: radial bin values for halo lensing profile
-           M: halo mass
-           c: concentration
-           z_l: lens redshift
-           z_s: source redshift
-           delta_sig: If False, return convergence profile, if True, return delta Sigma profile
-        '''
-        
-        if np.all(r_vals.value) == None:
-            r_vals = self.r_vals
-        
-        cosmo = LambdaCDM(H0=self.H_0, Om0=self.Omega_m, Ode0=self.Omega_Lambda, Tcmb0=self.Tcmb0)
-
-        r_200 = ( (const.G * self.M)/(100. * cosmo.H(self.z_l)**2) )**(1./3.)
-        r_s = r_200 * self.c
-        delta_c = (200./3.) * ( self.c**3 / ( np.log(1+self.c) - ( self.c/(1+self.c) ) ) )
-        
-        x = r_vals/r_s
-
-        Sigma_crit_coeff = const.c**2 / (4. * np.pi * const.G)
-
-        D_s = cosmo.angular_diameter_distance(self.z_s)  
-        D_d = cosmo.angular_diameter_distance(self.z_l)  
-        D_ds = cosmo.angular_diameter_distance_z1z2(self.z_l,self.z_s)  
-
-        Sigma_crit = Sigma_crit_coeff * D_s / (D_d * D_ds)
-
-        k_s = cosmo.critical_density(self.z_l) * delta_c * r_s
-
-        coeff = 2.*k_s / (x**2 - 1.)
-
-        f_internal = 1. - (2./np.lib.scimath.sqrt(1.-x**2)) * np.arctanh(np.lib.scimath.sqrt((1.-x)/(1.+x)))
-
-        nfw = coeff * f_internal
-
-        if self.sig:
-            return nfw.to(const.M_sun / u.Mpc**2).real
-        if not self.sig:
-            return (nfw.real / Sigma_crit).decompose()
-
-    def make_grid(self,npix,r_max):
-        '''make 2D grid centered on origin
-        npix: resolution of grid
-        r_max: width of grid is 2*r_max
-        '''
-        
-        npix *= 1j #imaginary so that ogrid knows to interpret npix as array size
-        y,x = np.ogrid[-r_max:r_max:npix,-r_max:r_max:npix]
-        r_2D = np.hypot(y,x)
-        
-        return r_2D
-
-    def kappa_NFW_2D(self,npix,r_max):
-        
-        '''create 2D NFW profile on grid
-        '''
-        
-        self.npix = npix
-        self.r_max = r_max
-        r_2D = self.make_grid(self.npix,self.r_max)
-        
-        return self.kappa_NFW(r_2D)
-
-
-
-def KaiserSquires(Sigma):
-
-    kappa_tilde = np.fft.fft2(Sigma)
-
-    k = np.fft.fftfreq(kappa_tilde.shape[0])
-
-    oper_1  = - 1./(k[:, None]**2 + k[None, :]**2) * (k[:, None]**2 - k[None, :]**2)
-    oper_2  = - 2./(k[:, None]**2 + k[None, :]**2) * k[:, None]*k[None, :]
-
-    oper_1[0, 0] = -1
-    oper_2[0, 0] = -1
-
-    e1_tilde = oper_1*kappa_tilde
-    e2_tilde = oper_2*kappa_tilde
-
-    e1 = np.fft.ifft2(e1_tilde).real
-    e2 = np.fft.ifft2(e2_tilde).real
-
-    return e1, e2
-
-def getTangetial(e1, e2, center, dx=10./1000.):
-
-    n = e1.shape[0]
-
-    xx = np.arange(-n/2, n/2)*dx
-
-    XX, YY = np.meshgrid(xx, xx)
-
-    center_1, center_2 = center
-
-    from_cent_1 = XX - center_1
-    from_cent_2 = YY - center_2
-
-    angle = -np.sign(from_cent_2)*np.arccos(from_cent_1/np.sqrt(from_cent_1**2+from_cent_2**2))
-    radius = np.sqrt(from_cent_1**2+from_cent_2**2)
-
-    angle[np.isnan(angle)] = 0
-
-    et = - e1*np.cos(2*angle) - e2*np.sin(2*angle)
-    ex = + e1*np.sin(2*angle) - e2*np.cos(2*angle)
-
-    return et, ex, radius, angle
-
-def getRadial(radius_map,r_bins,angle_map,phi_bins,kappa_map,et_map):
-
-    _N = np.zeros((len(r_bins)-1, len(phi_bins)-1))
-    _K = np.zeros((len(r_bins)-1, len(phi_bins)-1))
-    _GT = np.zeros((len(r_bins)-1, len(phi_bins)-1))
-
-    ii_r = np.digitize(radius_map, r_bins) - 1
-    ii_phi = np.digitize(angle_map, phi_bins) - 1
-    
-    for i_r, i_phi, kk, gg in zip(ii_r.flatten(), ii_phi.flatten(), kappa_map.flatten(), et_map.flatten()):
-
-        _N[i_r, i_phi] += 1
-        _K[i_r, i_phi] += kk
-        _GT[i_r, i_phi] += gg
-
-    kappa_radial = _K/_N
-    gammat_radial = _GT/_N
-    
-    return kappa_radial,gammat_radial
-
-
-def plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map,ex_map,
-                       kappa_radial,gammat_radial,r_bins):
-    
-    fig, ax = plt.subplots(2,3,figsize=[9,6])
-    ax.ravel()
-    
-    ax[0,0].imshow(kappa_map,origin = 'lower')
-    ax[0,0].set_title(r'$\kappa$')
-
-
-    ax[0,1].imshow(e1_map,origin = 'lower')
-    ax[0,1].set_title(r'$e_1$')
-
-
-    ax[0,2].imshow(e2_map,origin = 'lower')
-    ax[0,2].set_title(r'$e_2$')
-
-
-    ax[1,0].imshow(et_map,origin = 'lower')
-    ax[1,0].set_title(r'$e_t$')
-
-
-    ax[1,1].imshow(ex_map,origin = 'lower')
-    ax[1,1].set_title(r'$e_x$')
-
-    
-    
-    r_bins_mid = 0.5 * (r_bins[1:] + r_bins[:-1])
-
-    ax[1,2].plot(r_bins_mid, kappa_radial.mean(axis=-1), label=r'$\kappa(r)$')
-    ax[1,2].plot(r_bins_mid, gammat_radial.mean(axis=-1), label=r'$\gamma_t(r)$')
-    
-    plt.legend()
-    plt.show()
-    
-    fig,ax = plt.subplots(1,2)
-    
-    ax[0].imshow(kappa_radial,origin='lower')
-    ax[1].imshow(gammat_radial,origin='lower')
-    
-    ax[0].set_ylabel('r')
-    ax[0].set_xlabel('$\phi$')
-    
-    ax[1].set_ylabel('r')
-    ax[1].set_xlabel('$\phi$')
-    
-    ax[0].set_title(r'$\kappa$')
-    ax[1].set_title(r'$\gamma_t$')
-
-    plt.show()
diff --git a/examples/demo_model_profile.ipynb b/examples/demo_model_profile.ipynb
index 0740abaa2..c37bdae21 100644
--- a/examples/demo_model_profile.ipynb
+++ b/examples/demo_model_profile.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 1,
    "id": "45308159",
    "metadata": {},
    "outputs": [],
@@ -14,76 +14,147 @@
     "import matplotlib.pyplot as plt\n",
     "import sys\n",
     "from astropy import units as un\n",
+    "import os\n",
+    "\n",
+    "os.environ[\n",
+    "    \"CLMM_MODELING_BACKEND\"\n",
+    "] = \"ccl\"  # here you may choose ccl, nc (NumCosmo) or ct (cluster_toolkit)\n",
+    "\n",
     "import clmm\n",
+    "\n",
     "from clmm import Cosmology\n",
     "from clmm.support import mock_data as mock\n",
     "from clmm.galaxycluster import GalaxyCluster\n",
+    "from clmm import dataops\n",
     "\n",
     "# profile modelling package\n",
     "import clmm.model_profile as mod"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "7ba07a0d",
+   "metadata": {},
+   "source": [
+    "Make sure we know which version we're using"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 151,
-   "id": "65ddbc40-cfa4-41b5-855d-4418b867f9c3",
+   "execution_count": 9,
+   "id": "bbd94d3a",
    "metadata": {},
    "outputs": [
     {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "WARNING: function 'sqrt' is not known to astropy's Quantity. Will run it anyway, hoping it will treat ndarray subclasses correctly. Please raise an issue at https://github.com/astropy/astropy/issues. [astropy.units.quantity]\n"
-     ]
+     "data": {
+      "text/plain": [
+       "'0.16.0'"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
-    "# r_2D = lensing_map.make_grid(npix,r_max)\n",
-    "c = 4\n",
-    "lensing_map.c = c\n",
-    "rbins = np.linspace(1e-3,50,npix)*un.Mpc\n",
-    "lensing_map.compute_sigma = False\n",
-    "kappa1 = lensing_map.kappa_NFW(r_vals=rbins)"
+    "clmm.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "66c330d7",
+   "metadata": {},
+   "source": [
+    "The modelling module can be used to create 2D lensing maps. This allows us to forward model systematics, starting at the map level. In this notebook, we use miscentering as an example systematic."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 249,
+   "id": "909edd57",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# specify parameters for NFW halo\n",
+    "c    = 3.5  #concentration\n",
+    "z_l  = 0.5  #lens redshift\n",
+    "z_s  = 1.0  #source redshift\n",
+    "Mass = 1e14 * un.M_sun\n",
+    "\n",
+    "# define physical size of grid\n",
+    "r_min = 1e-3 * un.Mpc\n",
+    "r_max = 3    * un.Mpc\n",
+    "\n",
+    "# number of pixels in grid\n",
+    "npix = 512\n",
+    "\n",
+    "# define physcial size of a pixel\n",
+    "dx = r_max/npix\n",
+    "\n",
+    "# define the center of the map (in Mpc)\n",
+    "center_1 = 0\n",
+    "center_2 = 0\n",
+    "\n",
+    "# define radial and angular bins\n",
+    "N_r_bins   = 30\n",
+    "N_phi_bins = 25\n",
+    "r_bins   = np.insert(np.logspace(-2, np.log10(r_max.value), N_r_bins), 0, r_min.value) * r_max.unit\n",
+    "phi_bins = np.linspace(-np.pi, np.pi+0.01, num=N_phi_bins+1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4e244831-d6ea-4e45-a0cf-1eb80979cb6b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "de3d76d6",
+   "metadata": {},
+   "source": [
+    "Now we can create the convergence maps"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 152,
-   "id": "7a41267c-0d79-40b8-b906-d9a7e7f3f2c2",
+   "execution_count": 250,
+   "id": "5b51bbc8",
    "metadata": {},
    "outputs": [],
    "source": [
-    "kappa2 = clmm.compute_convergence(rbins.value,Mass.value,c,z_l,z_s,cosmo,200,'nfw','mean')"
+    "# set cosmology\n",
+    "cosmo = Cosmology(H0=70.0, Omega_dm0=0.25, Omega_b0=0.05, Omega_k0=0.0)\n",
+    "\n",
+    "# lensing_map has the option to return either Sigma map or the convergence map\n",
+    "lensing_map = mod.profiles(cosmo,mdelta=Mass,cdelta=c,z_l=z_l,z_s=z_s,\n",
+    "                           halo_profile_model='nfw',delta_mdef=200,\n",
+    "                           massdef='critical',compute_sigma=False)\n",
+    "\n",
+    "# make map\n",
+    "kappa_map = lensing_map.kappa_or_profile_2D(npix,r_max) "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 173,
-   "id": "f0554ee2-7c65-4385-a04e-773bbce666da",
+   "execution_count": 265,
+   "id": "4dff16b1-28de-453f-bdbd-e5972eb434f8",
    "metadata": {},
    "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x16cccd660>]"
-      ]
-     },
-     "execution_count": 173,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
     {
      "data": {
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        "  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
-       "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"402.02pt\" height=\"297.190125pt\" viewBox=\"0 0 402.02 297.190125\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n",
+       "<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"384.489537pt\" height=\"314.667469pt\" viewBox=\"0 0 384.489537 314.667469\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n",
        " <metadata>\n",
        "  <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2025-04-01T17:26:00.461220</dc:date>\n",
+       "    <dc:date>2025-06-10T13:55:35.853838</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -98,73 +169,42 @@
        " </defs>\n",
        " <g id=\"figure_1\">\n",
        "  <g id=\"patch_1\">\n",
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-       "L 402.02 297.190125 \n",
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+       "L 384.489537 0 \n",
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        "  <g id=\"axes_1\">\n",
        "   <g id=\"patch_2\">\n",
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-       "L 37.7 7.2 \n",
+       "    <path d=\"M 42.620313 277.111219 \n",
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+       "   <g clip-path=\"url(#p0782a28b6a)\">\n",
+       "    <image xlink:href=\"data:image/png;base64,\n",
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+       "<Figure size 640x480 with 2 Axes>"
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+   "source": [
+    "axlim = r_max.value\n",
+    "plt.imshow(kappa_map,extent=[-axlim,axlim,-axlim,axlim],origin='lower')\n",
+    "plt.xlabel('x ({0})'.format(r_max.unit))\n",
+    "plt.ylabel('y ({0})'.format(r_max.unit))\n",
+    "plt.colorbar().set_label('$\\\\kappa$',rotation=0,fontsize=14)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e073090a",
+   "metadata": {},
+   "source": [
+    "Repeat the procedure for a Sigma map"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 252,
+   "id": "2aaf9cb0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# lensing_map has the option to return either Sigma map or the convergence map.\n",
+    "lensing_map = mod.profiles(cosmo,mdelta=Mass,cdelta=c,z_l=z_l,z_s=z_s,\n",
+    "                           halo_profile_model='nfw',delta_mdef=200,\n",
+    "                           massdef='critical',compute_sigma=True)\n",
+    "\n",
+    "# make map\n",
+    "Sigma_map = lensing_map.kappa_or_profile_2D(npix,r_max)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 253,
+   "id": "72993065",
+   "metadata": {},
+   "outputs": [
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-    "plt.loglog(rbins,kappa1.value)\n",
-    "plt.loglog(rbins,kappa2)\n"
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-    "lensing_map.compute_sigma = True\n",
-    "Sigma1 = lensing_map.kappa_NFW(r_vals=rbins)"
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+     "metadata": {},
+     "output_type": "display_data"
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+   ],
+   "source": [
+    "axlim = r_max.value\n",
+    "plt.imshow(Sigma_map,extent=[-axlim,axlim,-axlim,axlim],origin='lower')\n",
+    "plt.xlabel('x ({0})'.format(r_max.unit))\n",
+    "plt.ylabel('y ({0})'.format(r_max.unit))\n",
+    "plt.colorbar().set_label('$\\\\Sigma [M_\\odot\\; Mpc^{-2}]$',rotation=90)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4b28b017",
+   "metadata": {},
+   "source": [
+    "We can transform from the convergence to the shear with the Kaiser Squires algorithm, returning the e1 and e2 shear maps."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 254,
+   "id": "eec34ea3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:230: RuntimeWarning: divide by zero encountered in divide\n",
+      "  ---------\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:230: RuntimeWarning: invalid value encountered in multiply\n",
+      "  ---------\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:231: RuntimeWarning: divide by zero encountered in divide\n",
+      "  et,ex: arrays\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:231: RuntimeWarning: invalid value encountered in multiply\n",
+      "  et,ex: arrays\n"
+     ]
+    }
+   ],
+   "source": [
+    "e1_map, e2_map = mod.KaiserSquires(kappa_map)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "25f42de1",
+   "metadata": {},
+   "source": [
+    "Plot the e1 and e2 maps"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 255,
+   "id": "2ba6da86",
+   "metadata": {},
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     }
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-    "plt.loglog(rbins,Sigma1.value)\n",
-    "plt.loglog(rbins,Sigma2)\n"
+    "plt.imshow(e1_map)\n",
+    "plt.xlabel('x ({0})'.format(r_max.unit))\n",
+    "plt.ylabel('y ({0})'.format(r_max.unit))\n",
+    "plt.colorbar().set_label('$e_1$',rotation=90)\n",
+    "plt.show()\n",
+    "\n",
+    "plt.imshow(e2_map)\n",
+    "plt.xlabel('x ({0})'.format(r_max.unit))\n",
+    "plt.ylabel('y ({0})'.format(r_max.unit))\n",
+    "plt.colorbar().set_label('$e_2$',rotation=90)\n",
+    "plt.show()"
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-   "execution_count": null,
-   "id": "bd3eb025-713a-4b7e-90ec-148503994a6d",
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-   "outputs": [],
-   "source": []
-  },
   {
    "cell_type": "markdown",
-   "id": "7ba07a0d",
-   "metadata": {},
-   "source": [
-    "Make sure we know which version we're using"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "bbd94d3a",
+   "id": "12c04b61",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'0.16.0'"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
    "source": [
-    "clmm.__version__"
+    "from the convergence map we can compute the convergence profile, and from the e1 and e2 maps we can compute the tangential shear profile."
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "66c330d7",
-   "metadata": {},
-   "source": [
-    "The modelling module can be used to create 2D lensing maps. This allows us to forward model systematics, starting at the map level. In this notebook, we use miscentering as an example systematic."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 42,
-   "id": "909edd57",
+   "id": "f6af6b7e",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "# specify parameters for NFW halo\n",
-    "c    = 10   #concentration\n",
-    "z_l  = 0.5  #lens redshift\n",
-    "z_s  = 1.0  #source redshift\n",
-    "Mass = 1e14 * un.M_sun\n",
-    "\n",
-    "# define physical size of grid\n",
-    "r_min = 0 * un.Mpc\n",
-    "r_max = 50 * un.Mpc\n",
-    "\n",
-    "# number of pixels in grid\n",
-    "npix = 512\n",
-    "\n",
-    "# define physcial size of a pixel\n",
-    "dx = r_max/npix\n",
-    "\n",
-    "# define the center of the map (in Mpc)\n",
-    "center_1 = 0\n",
-    "center_2 = 0\n",
+    "The getTangential function uses the e1 and e2 maps as an input, along with a map center, and returns e_tangential and e_cross maps about a given center. \n",
     "\n",
-    "# define radial and angular bins\n",
-    "N_r_bins   = 30\n",
-    "N_phi_bins = 25\n",
-    "r_bins   = np.insert(np.logspace(-2, np.log10(r_max.value), N_r_bins), 0, r_min.value) * un.Mpc\n",
-    "phi_bins = np.linspace(-np.pi, np.pi+0.01, num=N_phi_bins+1)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "de3d76d6",
-   "metadata": {},
-   "source": [
-    "Now we can create the convergence maps"
+    "The function also returns a radius map and an angle map, which is used when computing radial profile with getRadial"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 85,
-   "id": "5b51bbc8",
+   "execution_count": 256,
+   "id": "6b8c1825",
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "WARNING: function 'sqrt' is not known to astropy's Quantity. Will run it anyway, hoping it will treat ndarray subclasses correctly. Please raise an issue at https://github.com/astropy/astropy/issues. [astropy.units.quantity]\n"
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:273: RuntimeWarning: invalid value encountered in divide\n",
+      "  tangential shear map\n"
      ]
     }
    ],
    "source": [
-    "# set cosmology\n",
-    "cosmo = Cosmology(H0=70.0, Omega_dm0=0.25, Omega_b0=0.05, Omega_k0=0.0)\n",
-    "\n",
-    "# lensing_map has the option to return either Sigma map or the convergence map\n",
-    "lensing_map = mod.profiles(cosmo, Mass, c, z_l, z_s, compute_sigma=False) \n",
-    "\n",
-    "# make map\n",
-    "kappa_map = lensing_map.kappa_NFW_2D(npix,r_max) "
+    "et_map, ex_map, radius_map, angle_map = mod.get_Tangential_and_Cross(e1_map, e2_map, [center_1, center_2], dx=dx.value)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "id": "b0dc4b6c",
+   "execution_count": 257,
+   "id": "e743f1b8",
    "metadata": {},
    "outputs": [
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oy5reUlc+HyzkL7XYbXnX82LwM1JiYc3E4uQGRA4+yUnjPlIGN6/KKaEUHhK4bxA0hF1aCXhIL47Mjbh9MvcMgCYNfiaQfIdEF9wZcSog8oI0Gei8WEYR6aYu/25JJVPipxRu/833OBHpi3VSdi1c6V2sn9L9SOchmZt1ick8p8SSm8pLl1cafCrAgGdZIHIOcKrX10jjvr/75okbibulFDedewSujWCv+qE1adr/ttL221EHJwoJ/aPUYst8b9c3ABrcBi1SeQtQXmEBRD4LJerjoU8DuQOcvnuZ2MLe/6Y9YrdlfyTvhT6SfSiVKyNErYm+dp+u2+uU1m+hO246ZG7XxGMypxsDnymP58BJ+KAqc4qcUwLOoXdZ5fTayA2drkoq7u+hcoqyfhypHwncJ/XIuh3Bdt37pvVRXtGreid0U3KxZHpK5m6ZxbzOGfwMytyXyp+kW4HllSpM+gmhrsifiAK0505ZJXdcwC2puDNdLiTuFbiTyHW0S4qUpk3UZBK5OoRuEvrRhJPOP2RutoGd1rO/SPlamqzLK+CazBNtLnMm8gqwvqKzdFklJY0fDwfSuO//GRLXy+IIfevjkcxDb4cm2jy+pW2llSVwRWpdiRYrnRPFZU7kv3ui+b97TxZ3m8VS+eDlFQx4lgMin5Xan5Z8Jzb3hOLWxX1tuBJfFud3egtc0TmRu22bi3aOiSq7SFfahE4raVr2Ovr6KfNXaJ64U2Ix6+oKNFYrL0Hl1Af4ApH3hmm9vkRZJSmNW499pPGQxL/2x7/eAj9eu1A4lRvDa73VyHeJH8mZli2dv4jUssXwk8ytfntLLPZzUlO54U55hQuT1qU5AZEPwuNvgYmVX3LLKjlp/KKkEpX4Yr122WR+iF15+rHqPY0rUosmtW7SV6t+e/dF22wWn8xNLXzno8RyJ5U/Ka88LJuwPTGAbCByKXCuwce4SuM+7JKLqYl7JK6X7TEjcL1sr93+b5a5/6uJ6Gsb6FSr3h26CZ1WInpZ3bRlrhTRore/m5NKqMTirnPK5fuckTpzZUIg8tGpde/xnKmQsTRO9JnGtwb2dH0e2PRKfLEfN+3ZN8Pam9zvbaVWIrXuktoFrmhz/fHcF22DnrSQWlfSewnevUOiXojUS59PPIFU3m3KH+MBT1CG+UTOtCbdlItUnFWmSSmrxJbpPu6WVOzSiiPx9WvZxP1tOQSuv9E7nat3WVxpIjIS10Tqx/77okj9WEkpRQutZ5mb6SpavWey+FJ5KHGHHk8prwS4PBlITf8lmbBmP5/IwX1yT4K5JwR3cNRO5YqO38lO398W0l+bxNdv6vh9E7uziNX6UUTLD9oNvxD9WLfaOdE2RVFtf1P7sreTm3OzLKJ0aeYKdkIZgftA5CB9oPMpzrzw0yCn/Ryicxo/XkfvUsqiDolvAt9Evn7R9tjXO5UT0ZHGl5cm9VLbKquthLLQJnN9DDDSNgVxUVu9ZdFHKj9q5Sa77+n/c9CTyiXjigOeYAwg8gKwvhioA9H6ePhF57KKJ40fs1OOWjkd9fH1m6L1G9HrN2qXO3lFrn+orf79XZMpnuhduts3BxGpRZPWylw5dErl2/VD5pJ7SpN1Tp18MnBRUBkgcpBP6RPXR53cszxFR4I/BL4Ygb8lvv52k/j6G1Nm2Rexbulbf9dbSeUY3tyEvej9ubvE1Upb2cVNwwtt6bzWjBTMFAE3gMh7Umjg9fEc8lLkDnS6f3N/t6ce2hf7HPVxU0Z5S/z1W0Wvn+gQuv7am3ttNfHlH4q+fiV6S1wfs1n0ahIi7dMSrfq4Ka+cLsf3/O5bv9iAZ2eKfUJATb8rEDm4z53ZLRan793cf3dvP3tcjHkMdlp1cpPQTV38G9Hrp/3nn4heP2nS3/bL8n8o+vpVbVPRtZXQv4j0ay/f7AOkSul9Wdudy4+ph0ef1Lu8ss9e0YvapiG661xrMBQAC4gcPCd2tWfwNfGUfqRwopNFtZlSaIl3/VJHOWX97SbxH39Y6fWHF6nfvbZZKL98kf75i4iWTeSvTbzbwKc+TVc8iVvZfbJmr4TWKXdqIJIsKABEDtrhflFEDnsaP5K7Ee9i/RypXNPrDy/6/T//nf78p/8jIqK//u2P9Hf6Panvipbv7/q5Xs4nBnX000wxzEzJoQuDAKgIRA7kYZVbjv+rt8z1N03qdy/685/+j/7zX/6HiIj+63//nf7y80+kv30dM17Iev3HJf0ACAIiB2Oyh+GXe1UQAAMCkQN5mMki2vq/NYCpfijSv3zRX//2R/pv+jci2kor+pcvUvs88u37N9+vP7UFgDAgctCOVb/niOfWyfU+/W/V210MdxGfLrvfpxh+/apI//xFf6ff019+/ml7+S9f9PXzF339qmj5QYfMzb1XTFtHPzXdm0VivsAZ9XHQEIgcPGebeO08puOy1vs87sDflDb3CFenlKz29KwtiS8vTfqH2i72+cc2xZBoIfVdkf62TSQ/ph/+QvT1K9GyXxi0vPTRjknmynawPvcpKvcr8fv+jhkroAAQObjPlawvnqvW/bJ4onfS1pq0JXiljyvlt8vo9fZFEMddDFczldCk8beMt9kpW1v235d/EC3f91T+2vqhtN7b1bvQ9SF05fhXGSFbqVv5EnhOoscccvAAiLwnviR7p5n9q8S6s2r/1Z0x4bt3ErR/X/eLcrT15cjL/qUQq9puRav227l8NwlfH3L3XaK/fNe0fN9E/vVd02Jkvt/Wlnapm/uoHCncva9K6Hff+oW2FQOK3fcFnyy6ApGDfELCvosr+pWIvpzlqffl9EpttXK1mlvREpF175QtaWvvTbNMffzLlFZ+aFp+vNP4VmbZ5a3pU7gxoZeAieCBLCDyAuhV4w6IFqdPCOuadgfE44uQ98vi9/LG9q86/q7N17O9tvuikNL7rWiJaL93iv7aErnviyW229gSLa9N4tvVnSbF76WV1Sq37CUdk8xPZZVUiVu3mcWdD8/gzodlgMhBXLYl07eRtbUotZqrNJ3yirn74F5eMd92b0RLRKR+bI0tpPdb0e7tmcvu9wuFtnatmvq6y9wk8UPm71r5kcbtsorxsZPI3wnemrFSUtgx2eFe5IAgcpBDbk0/dzCUiEyqPkopTirXmrY0TnuJZZc5ab3doHCfpRj/qje918TtJL6XVF578n6tH2n81M+rGSzB9Ut9PgQN0plP5IUGGEVzIdiswdNDuvt2zR3wdKch7nPNld6+I/NI5bTuXwOxv4xo+45NrUjr9f1FEyud7sNi8557rq1kbs1WsX5Xmra0a6VxZSfuj3UIbBsf5vVG1hmSvyzNoHQz5UlwPpHPRmqNOrvdeMklWid3LgxSq3aku6dxMvPFV9Kb3bdv9zHLIOsUoIlo2cYqzI2wjjFQ83cy5RV9DJaacspJ4q93SUWtqz+Vm5r56jzmllVy6uO16sUovwwPRC6F0jNFWuFOKSS6LrcY0Zta+bKXWF5E9EUnme/R/Ph6tu1L6ff6uLu9TNLeB1LtgU0j5UPiL2fqoel/qmxrzmxpBQYixQCRD8LjueSpA56xqzhj5ZVYKidr0PP4O71nsJjSyrJ8yNx8h6b5eja1bF8KsaVxtwSyL8ueJ24uALJq4ofE99KKctO2ncbdQU53nX3b0mxHs+1c7NJAxYFOzKAZB4i8N0xr9kknhtTyylUq3x/7kLl5nDwyX/RWMzffq6npPMvFXYbdnhG2NlI/18S9EtcRibvL8KTxEmUVtuKdsCbNDYh8VnJmlGS1eyOVh/phpfaTzJXaaub774fEF+XUxn1pd2/PFrhVQjE18Q+Jx0R7N42XhqvoQXUg8kKwviioxIBnanmF3IcTUrklIG+JxZX5onfhqr0Wrt9Xe+5fyRbjkLdZ9oe0PRKPlVTsbZCTxp+UVVJhPNCJi4HKUVfktVIfqIMj/BLllegyTK16OQv9Sub0orPAtSXvZb/lVuzeLqZNCgjcPO9K4vY2CMxUSdsmN8oqjAUNPFT+tDRnImdal74kZ8pfCk9OtBmDnsFUfkxPtEosIZm/9ufv3/v5LrXot9CJyBg9lMpPojb/eqWuz8/xSdz3PHtbkCXg3EHOXDJF0W0qZG0mrdfPKfIZKV1euXo8JHO7L3aJJUXmRO90btpTykro9H7tVSLf2/pI4GZ9HGEHJe6265s3HquNh4Q5eFkFlAUi5wCnTwh3yis2Vynf/P2JzI90/m5vS9MmjZs7IfrxpnIibwrf+hCR+OkEkHil5tP0zEnQkyZgbkDkBWky4Nm7vBIa9MxJ5a7M7X4EZE4UETrty7alnrLept/2/90Ubh4LSfzYLmeJZ6fxJ4OcAssqGOgsC0QOPqmRyq9kfnrsU+ZEgXR+tH8s/Hrw1VcScf5Vbjo3//rEfyVxm1ZpnFNqB9WByLnQorxS6r4rKancHfi0yJK5w0c6P5ZjnTxeibL0DFIGU7hZP/d1IYmfluMpuZRK4z1BWYUN84qcU126MGUSdEYqzyyxeJftnmQOmauzrM2fX+8+f0g9dZ1NW75SSUziKTXxOyWVjy4mpPHSZRXJTHxiqS/y3BosuObJDbRqpPIQ9nsfm8USGgAlepdM3C57auh7Y6Qv+vXxRcmpAj89/inxaF08RaCl0viTsoqkTwRSaHDynDeRV4L1FZ4x7qTynBKL/ZxUmbulFiJvucXFTuve9Yw95qtvl5R4YkmlRhrnAgY6ywORc6JguSdaCql1j/IUmR99eMuciPw1c1dUOUL3LTMkvqBoPSWXWE38anAzsaTyiEgaL1pWmbiMwRGIXCo17k/+NJXH+ugb/LT+7h0AJboWOlFSSj/6EOqn7zk+gVuPByV+NbgZW77brrtsX99KgaQslrlFXmnAk0t5pVYqTy6xfPzNkjnRxwDoSeZE10I/lhHo6MdVoQmJ3P2/R+Cmrx/tppRT3OddSTyHVmn8AdXKKpN/Qmgjcgx4ppNzcumUyq/biKxDqGZO5C+1bP/xC91z98TT46ni9j2eI3CzLlftu89LgWMan1yaWTQ6gY45/w4cRJNYKMF5p9OtzlPcj//pqfNcvvA/79S+O+XPrlO7P6HHU54Tat/Xp1SJx+riJUsqAtI4qMfcpRXwiMt6uVsPJ4rPZnGed0rn5jXbA5/isi/1zyFBltEBzTvlFM/fZ5AtZqvUAyLnWCcvXF65VStPLLFkydz9uytzouBAKJFH6NuD7749wSPS6KcOV8ylJd4yjUsvq3DsU2MgchCmlcyJ/EI/zUxRJyl5pW6TM4/cWZcTV1LOfX5piQNAqJFX5dFHyZyUkbCcW7XyJ8/PFNrnzBHP850auv3zQaw+fnpaoB1ned4+PZS4l4LvBac0jrJKXdolcs4zVwa+70oyOSUWz/O95ZuUZE50nc6JPmvo9uuoUI3Ze0FPQjpOeZ3nOcl3NrxRUpkGzmWVhp+iUFrhTMtaefyFSSfhZJkThUstZnlE52WGXueSOi5xlRBTBO5rJ/FbgJJPPDdlwCmNg/pA5JXhcnGQoehFQin1ciL/SeYqnW+Nbf/6hE7kP8nVKGelCDz0+lSJty6pNARllfpA5IYRyislLhB6WGLZnurMMjF9I0pL5x/P88xSsV/vI3hBUqIwg+WMwgIn6lNSGSGNc+1XB9qai1lSEEH2lYAPBz6JionFnzwzRBi6CVVg4PKjTd9P9DWRtoP94SXx4iWVh0ybxhu7Dom8AY/LKxU+LRSvlweSfLDUQnSdzu3nus83ffFxtV6pB1lMQokC3xZXSOIXVCmpIPWKACK3GaG8QlS3xEIUlzlRWt081M9YDTwmdbd/d8mV98XrsuvhJaeJetsYJCHjBHOivcg5T0OsiMhUfkfmgdd56+ZE/nR+vCiQ0u3X2eRu31SplRI4UTWJc0zjKKu0A4l8VBJTeUuZR5eXInSi+MmspDiuJBZZFluJzyrWCRigjlCYih/ZHieUCgOfRA8GP7cXZ78ueDUmUXhQ8XhxxuBlDqntRvoXXy9hEuecxlFW+QCJHKTxJJkTBdM5kafcQpRRD29wUF9I6dHtD2rXxMEU9Enk3KchIpUH2rpIlTelFE2yRO8U3LI0kLDM637X2V728pNAGm9HJ7chkUskd+CzVL2c6Prqz5vp3CyfKJDQjzYKDHKmtBnhUSlqa+DZ61P6cLTVVuKgDxB5B7pctt9a5kSPhb41kbCdGiT1x59Ytkaet5HaF6Iug5vTzlTpTL/BzonLK0W4079WZZZ3Q9dtJAzmXZYwKpG87IT1ECHxEff5lnR0GhJ5J4qk8ooXMCUnc6Jn6Ty1HfqU2K0rUzPav6TEySy1Hao0V/xo/Lkkkcb7AZHHqHylJ+cSC1HGZfwpd01MuRAsUeh2/7qQOpukl8RHLKlwT+Od6TuPnHt5RQIVSyxEOR/lE9NpqtxSyhUtyelTznomUF3ikORzOrsMifwKCan8Th9rJXOitHROlHarBld2OfdLf8Kdk0jJk97RJH+JI433ByIfhQYyJ0qdRZJQatkapb3RpD4cbbs8lfvT5J8l20r1cCTxqekvcgk30ZKQyu+SeafE4ul8a/T9+519oUcJpsbA6NF0A4kXAmmcupdViHrXyMFBkQPi7k5f+oKYU9uZte7UL47owZ2+Za5/M4lLKKmAZPonciKk8pLc7eeNZE6UMQUwc0bKvpD37732j7snlMxPCbdm4HSUeBMk9JNJ4OAhckBEBUssjWROlFFqOZZxQ+jbgj4fKy33EgfljTKPRIkjjfMCIs+hQSqXKnOizAt07gr9vOD7ry1NK4ETzSFxCWmcEXxELqG8Io0nMieqn86JzgJsNbWwFA8GWZumcCJZEpcCoyDBR+RSkJTKt8bu97dVOj+WJ0DqD2fINE/hRPLSrbT+MoDX0cLoDBelwY5WNPk86e/Nfjy+0RWnqzsL9OXR9mAicZRULJi5ComcMZKT+bHYJwn9WH6Fi4BylvWAx/eDmUni4DYQ+V0aTUdkJXOivkI/9Yd3cusqcCKZEpeSxhnCq7RCxO4jy3A8PVgeHtS97i3eiiLrx0jiwAPD/ReJ/AkSU/nW4LN+P0znROfEWvq+4q0pdmLqeXVvsDmkcQnwS+RELM94QRrtgMUPqBL9LvSFyD2/BeguRftc6oulIfH6MN1HeYoceGEpc6KiN23iLPUqfSu17aRKHBSBb2lF0gVCDe/DUqXMQvS8/wXKLS4+YbYqw1Q/kTAV+NZkQ4kjjReBr8ilIVnmW6Nl+l9B6DZXgk0Vfb+viWNyfUCwSUhcIrxFLimVN4a1zImqCz0Ex5IMEZW/Z7h0iUuD6361w1vk0mh8q9tqMicqL3Si5lLvTg0xVkqxzSWONF4U/oOdzM+EHzTeQasdgDXWo9TsDO7UWk9IvA8CHIREXoMRkvnW8PZv6XUZMaXXlGFF8UHiYyBD5KiVX1L1ez9rnphckUgR+wBzrFETT0BAGieSInKJdPhquOoyJ6q/TpzT+kAzOrpIHGm8GnJELjGVjybzbQHbvy3WKySb2oLvmVSl3SI5faHtl/kUIWmcSJLIpTKizLeFbP/2+ELqEUsCUm/1kLbQ9sucDFkil5jKO2EO2KGFPgIjC1wygtI4kYTphy7CNjARdU0kTW98hOSVTsPt1VXiEvcJgY6RJ3KpzCDzbWEyD95WNN4+kPgcyCqtGKSWWDrUy9+LblRqeS+Q9gW2WR53RrlQLL0DfZd/F4FpnEiqyCXTUebb4hsMhJ4X+P59Nql3khkkPh9yjyyhZ04i6r6jdzvQTVlh5AO98zpC4g8Q7BTZiVxqiYWIRTInalhq+ezA+f9S0zoTcXUX+NaJ3j24j2CJE0kXuXQ6y3zrQuNSS7gj79+5S52ZsCBxIF/kklM5ERuZE3VM5y4hKbTeTszlxELgROy30yXC0zjRCCIfAQYy37rBTOguKcJI3Y6C5cNG4ESityMRDSFxolFELj2VE7GRORGjcssdpIvlAkgc+OBhjhKMcGZldGDoVfOSxuSwez8Y7au3GcEZO+OInGiMN4bZAcJOIJPBcvsz20dvMYIrLMYorYwGozKLgX39fDDYydswgsQHhJctSjDKmZbpAcMyIQ4E6+3LdJ/MZhRHWIyZyEcY/CRimcwNtmyQ0p/BVtw2kDhrxhT5SAi4+RTKLveAwEEpxhX5KKncwDidG5DSrxEhb8NoEh80jRONLHIiyLwjSOlvRMnbAImLYmyRE40pcyJxQjfMInaR8iYaT+BEw0ucaAaRj4qgdG4zcvlFrLwNI0p8EuYQ+Wip3CBU5gaf+KTIXby0XUaV+ARpnGgWkRONLXMi0UK34Sj34aRtM6rAiaaRONFMIicaV+ZE4tN5jBSR3pX90JK+AhIfhrlETjS+zImGFXqMqYWcy8gCJ5pO4kQjXqKfwuhv9OgHKrjP6PvG6Md2gPkS+SxMnM6Bh9EFPjnzinzkEosNhD43Mwl80jRONGtpxTDTGz/TAQ02ZnrPZzqWPcybyA2zJHMipPNZmEngRNNLnAgi35hJ5kQQ+qjMJnAiSHwHIjfMJnMiCH0UZhQ4ESRuAZHbzChzIghdKrMKnAgSd4DIXWaVORGELoWZBU4EiXuAyH3MLHMiCJ0rswucCBIPAJGHmF3mRGdxQOp9gLzfQOJBIPIYkPkbpPS2QOBnIPEoEPkVkPkZpPR6QN5+IPFLIPIUIHM/kPpzIO84kHgSEHkqkHkcSD0dyDsNSDwZiDwHyDwNSP0TyDsPSDwLiDwXyDwPV2CziB3ivg8kng1EfgfI/D4+wUmXO6RdDkj8FhD5XcwOB6E/JyRCboKHsOsBgT8CIn8K0nk9rsRZWvQQdR8g8cdA5CWAzPsA8coHEi8Cs8+ugsEOCUAeOGaKAZGXBDsmAGngWCkKSiulwSAoAGEg8CogkdcCOywAZ3BMVAMirwl2XAA2cCxUBaWV2qDUAmYGAm8CEnkrsEOD2cA+3wwk8pYgnYMZgMCbg0TeA+zoYFSwb3cBibwXSOdgJCDwriCR9wYHAJAO9uHuIJFzAOkcSAQCZwMSOSdwYAApYF9lBRI5N5DOAWcgcJZA5FyB0AEnIHDWoLTCHRxAoDfYB9mDRC4BpHPQAwhcDBC5JCB00AIIXBwQuUQgdFADCFwsELlkIHRQAghcPBD5CEDo4A4Q+DBA5CMBoYMUIPDhgMhHBEIHPiDwYYHIR8Y+cCH1OYG8pwAinwWk9LmAwKcCIp8NpPRxgbynBSKfGaT0MYDApwciB0jpEoG8gQVEDs5A6nyBvEEAiByEgdT7A3mDBCBykIYrFIi9DhA3uAFEDu6BtF4OyBs8BCIHz0FazwPiBoWByEF5QqKaTfAQNmgERA7a4RPbKHKHtEFHIHLQlysBchE9RA0YA5ED3kCgAFyy9O4AAACAZ0DkAAAgHIgcAACEA5EDAIBwIHIAABAORA4AAMKByAEAQDgQOQAACAciBwAA4UDkAAAgHIgcAACEA5EDAIBwIHIAABAORA4AAMKByAEAQDgQOQAACAciBwAA4UDkAAAgHIgcAACEA5EDAIBwIHIAABAORA4AAML5fz9PCRIbImFEAAAAAElFTkSuQmCC\" 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      "metadata": {},
      "output_type": "display_data"
-    }
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-   "source": [
-    "axlim = 2*r_max.value\n",
-    "plt.imshow(kappa_map.value,extent=[-axlim,axlim,-axlim,axlim],origin='lower')\n",
-    "plt.xlabel('x ({0})'.format(r_max.unit))\n",
-    "plt.ylabel('y ({0})'.format(r_max.unit))\n",
-    "plt.colorbar().set_label('$\\\\kappa$',rotation=0)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "e073090a",
-   "metadata": {},
-   "source": [
-    "Repeat the procedure for a Sigma map"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "id": "2aaf9cb0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# lensing_map has the option to return either Sigma map or the convergence map.\n",
-    "lensing_map = mod.profiles(cosmo, Mass, c, z_l, z_s, compute_sigma=True) \n",
-    "\n",
-    "# make map\n",
-    "Sigma_map = lensing_map.kappa_NFW_2D(npix,r_max)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "72993065",
-   "metadata": {},
-   "outputs": [
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\" 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+       "<Figure size 640x480 with 2 Axes>"
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+   "source": [
+    "plt.imshow(et_map)\n",
+    "plt.xlabel('x ({0})'.format(r_max.unit))\n",
+    "plt.ylabel('y ({0})'.format(r_max.unit))\n",
+    "plt.colorbar().set_label('$e_t$',rotation=90)\n",
+    "plt.show()\n",
+    "\n",
+    "plt.imshow(ex_map)\n",
+    "plt.xlabel('x ({0})'.format(r_max.unit))\n",
+    "plt.ylabel('y ({0})'.format(r_max.unit))\n",
+    "plt.colorbar().set_label('$e_x$',rotation=90)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cde1c95f",
+   "metadata": {},
+   "source": [
+    "With the radius_map and angle_map, we can calculate the radial convergence profile from the kappa map and the radial tangential shear profile from the e_tangential map, using the getRadial function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 258,
+   "id": "e3d066a0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:324: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:325: RuntimeWarning: invalid value encountered in divide\n"
+     ]
+    }
+   ],
+   "source": [
+    "kappa_radial, gammat_radial = mod.get_Radial(radius_map,angle_map,\n",
+    "                                            r_bins.value,phi_bins,\n",
+    "                                            kappa_map,et_map)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f89da817",
+   "metadata": {},
+   "source": [
+    "plot the radial convergence and tangential shear profiles. Note that these profiles are not averaged over all angles yet, meaning that these profiles are 2D (radial and angular). This is useful for miscentering which leaves anisotropic signatures on the resulting lensing profiles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 259,
+   "id": "080ff2f4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, '$\\\\gamma_t$')"
+      ]
+     },
+     "execution_count": 259,
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+     "output_type": "execute_result"
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-    "axlim = 2*r_max.value\n",
-    "plt.imshow(Sigma_map.value,extent=[-axlim,axlim,-axlim,axlim],origin='lower')\n",
-    "plt.xlabel('x ({0})'.format(r_max.unit))\n",
-    "plt.ylabel('y ({0})'.format(r_max.unit))\n",
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-    "We can transform from the convergence to the shear with the Kaiser Squires algorithm, returning the e1 and e2 shear maps."
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-   "cell_type": "code",
-   "execution_count": 25,
-   "id": "eec34ea3",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
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-     "text": [
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:201: RuntimeWarning: divide by zero encountered in divide\n",
-      "  oper_1  = - 1./(k[:, None]**2 + k[None, :]**2) * (k[:, None]**2 - k[None, :]**2)\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:201: RuntimeWarning: invalid value encountered in multiply\n",
-      "  oper_1  = - 1./(k[:, None]**2 + k[None, :]**2) * (k[:, None]**2 - k[None, :]**2)\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:202: RuntimeWarning: divide by zero encountered in divide\n",
-      "  oper_2  = - 2./(k[:, None]**2 + k[None, :]**2) * k[:, None]*k[None, :]\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:202: RuntimeWarning: invalid value encountered in multiply\n",
-      "  oper_2  = - 2./(k[:, None]**2 + k[None, :]**2) * k[:, None]*k[None, :]\n"
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-    "e1_map, e2_map = mod.KaiserSquires(kappa_map)"
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-    "Plot the e1 and e2 maps"
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-   "execution_count": 9,
-   "id": "2ba6da86",
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       "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
+       "<Figure size 900x400 with 2 Axes>"
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      },
      "metadata": {},
      "output_type": "display_data"
-    },
+    }
+   ],
+   "source": [
+    "fig,ax = plt.subplots(1,2,figsize=(9,4))\n",
+    "\n",
+    "ax[0].imshow(kappa_radial,origin='lower')\n",
+    "ax[1].imshow(gammat_radial,origin='lower')\n",
+    "\n",
+    "ax[0].set_ylabel('r')\n",
+    "ax[0].set_xlabel('$\\phi$')\n",
+    "\n",
+    "ax[1].set_ylabel('r')\n",
+    "ax[1].set_xlabel('$\\phi$')\n",
+    "\n",
+    "ax[0].set_title(r'$\\kappa$')\n",
+    "ax[1].set_title(r'$\\gamma_t$')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1086e4de",
+   "metadata": {},
+   "source": [
+    "We can recover the 1D radial convergence and tangential shear profiles as follows"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 260,
+   "id": "5c6174be",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "kappa_1D_radial  = kappa_radial.mean(axis=-1)\n",
+    "gammat_1D_radial = gammat_radial.mean(axis=-1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ebb41586",
+   "metadata": {},
+   "source": [
+    "Plot the 1D radial profiles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 240,
+   "id": "29a26710",
+   "metadata": {},
+   "outputs": [
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Qb3HrPycfd79KAfrRMM/1rnOik7r6Gn6YELWP5dMgnuB7tx6ayBt66G5v6q35LTnVIpJ91FyIn32bfmr5nB0y5cToKv+g6MkrT426IK99KZSzXjOg2wLiuUD0lXP0Phat19F+Z3ruFZDve2Ba1XXCBm1kPqdsFyhDK7s1vH2RUi/3BBSaHyo7NXLrqpknWF7dA/p8j7zyNqpZT7sOUx7AkyMnD2NlBq+iOf50inXiaN5usVraK45yi9R4iU+fsow56yNlsTieNxC3Q3KtiBybJcPayOr07MBDPx/kNSPnpFAZmFEVHom0YYkJaVPK8DTTP1pl759zYe4dxeKCNQfgjDSs4zRXjadAPBfgtU5irvXLzRP0vSP++ZG+si86gG/NOMQjP0xd1izLayn4s5RAnG2fSPJpFZE6vG11WC27ch3fq1xlZnWKVV6JpRAP2Q9H2CtJVgojXcxqSZ1X22I5oqyD7LCb6+ysul0yYJ1cFhCEDAvgR8A7o263J54H89C05n1hgQr47+IsgLgPimd54yl1R73vTJjnlFcpbrHTM91aOVspp5Z1QB0lEM+pr1p6Ozi2hSPd3kYxfXOOvckawsidlxsclZhap2HHcE8K3LILNzj3KoZlpwTmh3YAX76a1seZdWSEo9spGn165AecEJPV+JEQ5y5/7fVklxeCqDV/Z4tavjnHC1/TOCC9HictAG7HUj5bmXFuFCq9MchVRmnY5ZXe5HMUzM+8WahTb/2mrBXvpqulxmuqes+OFh+WyCk7s02pEbN0PHaLmUa453Etlh4OmpAabw3xI8efcuuJXbkc4XEnjyRKm35r9ko9Rd7L7bSMqLWNgmOsU+utbbPE6rOLz7RVfOrcZ7V4lbkv761ELsRjJ4dYtQnrSnKLpfWHVDSQrs59G7hTpds0Ku7sza2Vmzmx1bJUakM84+o+J1z5vc8gXzM5pts2CS3MBXOaP+KH7+wVPb3keLDVtm2rpHbkcSGeAfAUaHPzR+HeYihhKsx7tFg6i5uyVpIix9NmRi8Qb33VHS0/ZIkgbLOEyljzJVtjCQd16aV5aJSKq/xMiAuxfVoEu/yjhhK25PJZzD+g3vM6O1MVcGo5DdviTpsI8UKAJ0dUefHrTHnaobMTVEi3xRJS5SkRKKe6gHMBunA8eRK0YztDwgLrer0qPaTOQ1ZLDUXdUpV7yvbe5Zl65XBA9DlqpVE0VeMpaTMhzq67Fuh9V9Ou49kGugVT1/EWslh2I1h89krN8NkqDPiyOjBDtgsKVXFKntjNaRygtxxO+Bb98sK4T2ulpUp3pk3pcQpMD9hBp9w0FCnTfUOQ5zuoZSIc0wraWBq1/HVgW6AEiAetjRb+GbNMVruc8xLbwk6bUG7LMjqM2wb5wcB27nMplkqGQo/66znwlo5PSp5YG22Yc9ebBfUd5I9UaTE1zvW5BaIQd5aTMhTQ/qQEo67glUIKzFP88lYnA28Z5UWcGW/GWkna1hxYNawrWkYLi8V7GR1Ia1kngMP3hvnb9MYdfjkjXFfeWVap61yS2wnq8sVzAB6rJ6VNdsQWLeCBB+2WGl43N+3DdnHGTSjyZifL0h2C+4IFX10tIF7bYgmV55hutN2ebyttYF2HPvVd5YTGCc5O5vPOSyHuU8S5KtsX3PJy1HmKqk49iXGi0dCtW7kxqC9FfrBVws1fvC1rQLwy0DL6wMx6Ah2dQXXuUuacsBX+EZGr8D0QdwK8oE7hyC9Tn58C+EeDAF51zlbmpQq6hSqvoeo7uzI4B+QHr4AmJ9Xc1535pvnyB9Jz1mMNSyh4Y5DDPqHlse7itC0WndYF79g0341HPoXM9XJjajyiMqMQD/DXBezUtEHA0220m+c+4xbDvJo/1lmcBPi+FHlKtFDJJ0ZS52hkXu0Tl11edNgh+R0bL+6FuVW//TCtFseL5AI+BHGH3WJAnAHwFHBzg5bphbpvpXrUuRfmZ8U9nAgy4yY88sOCa6tUVuPJI1wCij5prHnoEwjvsENp/Sbpd9Nj7eSmqxEFnrGzHA7EHV61EDIOcRH5cJoZqidUjiMPu9M29conJ29p3PA5oCnIb6SfoE20grgjogBPBDU3jxfodhkIw3zr6BT7tMB+GueEEYuUjjjXfEbHp6DTAmrfC9YcUCfkiQLdOb0yzN9KNF72+1LkR5w4UkaqRKIU4kGAp0CbG54yd+3wqPMUmLvS7L63CpeKDk2LQZyWS/sQXCBNVNesiJQZPJE4MzBhzm0bo/zqcWcnle498tL1nWQ15OZllMVWwcx8WaNbagath/jdgKeDc/nutDFpOl2kI509raZPzhpmxrzE90J8ne+Ad6jahIMg/jRDndBVj9z75770HD+65igWbodpg/A+c6WjuC9Fzo2KG58F+9yTRArEa6vvlLDqjtkgm/o2iwmqcledod+c2I0kYaTzjVLRI2VSIO5RyfSJhKlKl53XW3ei1WLVvZ+YeYLMjTfq575NkOcG56zM2W8zFbvXSull37VgbgDba6V4plvfg/YKc504N18I5j5f22Op7CBOYGnYF86OzjxwxyJargfmrJEzuRYLK00vO/VtRPfWyllRbT+qZKnUtFJKli31TUKh4Ye7YYWGFSOIV+Mpj2QriaCtEgN7COJ6UrCj01dv/Y3kvc3esxJ3VovT3si0WHLiICvlFuOhyAsi51gLjvLwTKthpWiFXHqCouWwRsrAo6wDNgtLlYciePMLs5CYGidpWBDfdXRaEGevWGbbA+W4LRCzfVtae2dkVJ/D7L4t6O7jociBij1mB5WRCPBq5bkOdC2afQciUd9rOp8yJ+nXxA5VbrS5FgBcIGPYLD6I+1Q46zZ9R/WhCG4+zwZKVefBNDmKu5a6fqh0AA9Fzo+cS8OYss6xIRMEJWtoYspBEMgXrY+kM6Z51LpXlTt+c+dtiRhpXGkp7F0NDEDcq8AdxXvEcbCJ0XyeDeRV50aa9B015YTFLfMR/nh7irzSvtFkH6sAfme+hLy+/NwXMXsVOlHQO28cgWmGnDfr8pXPihD1hNyr8ZClQuoVFtT36fbwDjbTsTFiD8ZyXbgY9XNutbeULssvL41qKj3jCuHG4zZB3uOJOgLdKJQTVKcvcjpEcyzjtdiA1REEug1zWNNIOlq/72QiRP4uIW1I0whYLeZdm3paAOIMgHOfsZICdycbHRuH89yUKMytjbQrs0VP9SMA3CrIG+8AXV7RxQ6yBBVea/loOQaAgb3SttvlAbdS4VZ+qspBp8NNxJxIUOcuONsQ96nw3bmh0sYIPRTL3jRGu4LgdWU6OXpsUwdxmyC/tyi0VLgQj44ySQ1LMQNuoEdhrsuiKtxhlaxprelVQ4PbpcY9vjgH4iyA50Dd+YhZVY4L6KUwP8RieURyPDo7D4hcr5uT1lm248Tghb0jfVLbrPy7uqRnOplnf3d2bp7heTpsF5cvTr+7HpRlJBPWzTalQw4D+V039jjXYrSjMrE9obIe0SSaKnI6euymIwaRElBbkbK+OCeI5I7P1La7rttp/2TIB1/yCV86u45WEe1xxN5Sob64C+JWsTt421UkLqP3pQ6AozPTVNFOqyWhg9D5TBZupPrk99Jx2ZiDD2slI6qenGpBlQNxX3kly2NfhtNpLqDHYI4tHQ3tlQtIw3VZv2tLgHvMC0dHJ7VVfJ2gti8egXgI4CVqlebdjzjZAz0Vvkl+eU175WHVZEX3IE85Nm8iAjtpkRqPzUu4akhpB/dtQcYoFY9v7u7otMqMNsg6Kdjh8r9DYavxZZowgK6/eCDOAHhKp+fO+/ZBfed/SyP/jpkxv9xqr/9NQ3eiopfo/cmHwA2A/M1GCmhTVT3XgmGEnU/adLDgTat3qfAQvA/lg0+NW52bFOIhFW7Du2S0SnCEyk5Ju+2WdTYSLJaHWo7HSevnHJC/oR2i+kiRSBmujsZQfVXaRy1Pmxv6ksqjzr2WysZKE+zSYa+4uOPqoIldxlBbBdt34bJaYhB3KXY6nxbFPDm51LFrhIrz9nsCaJdn7nVNAqrcTOgvpLt3e95hvD1F3ulJhCvQ2JZKBOLJnaCh2Hm0FtBtUzsC86A1Eqo/Va2n2izA6otzIO4DeK43buejcPQBnQtzsyLepU9Rp2fL6LFNjaMvkHcK2cODuw78/WjB8rjWTA2v3NXZGYU5TItlfy5YVLltV/gXxdFel7zFTplTNU47N3UjYxCPAbyGN24DPQhzuNOy193jGFXR2TroC+T3HoUbP6i4ffUkQryJV+7wx+l0zR27QzQauUrcDt8IFV9yar/AhHgM4C28cRvWQZgH1LZpY1H1nmGN3FmHZ+9xuyB3KYNKamFnr3a+U3oBn+Cfe/mSfACb5XnHkUszi3TMd7ky63dbvft8dq1aLX872P6AGqcQF9DT3So8BPBUoO/VuGml2OqcC/Nu7REddttqKeGa1mIHcRMg5wo0Z14byhXiFm90SoJ4bNlcJ1DXPI9XLuhvG9q2XeI7h9obIWcnsdN7NurOF0cY4n5v3Fe++TvUqanmC2O6D9jdQ9oVnR1XtzD0EDgA5F7o9eS1ndGWxPp8IOaocVZeX5s47WRs31UkE3CvWS2Yu0BvFEmtGFo4bY/v+BPWf/2dTveNVFkqdUHcVuHbb1uJe9oVSRPq2OTCnKPKffYKK27gOGoaqVe1FU8S9UDeuf1gRE8nEYTVclbUgLinHbErkd1DswCD0IZXrq0UksYF851al2Q+aAaShht0gXbQ3lsqMYi7FHhOJ2dqx6bLaonCPCHMkwC2k2tvqr+nthwY6SBvDcHOIHszkbDOghCP2S6JZe9uEAJMgMOvtA1YL20zAV7R47I7LO3OSgpxMp1aKbYKL+nktNPzvfAEsN6S+OopGvMpZ5e+CY/cGx5I2NOae9onnXxiy8RS+lzFHirD2wCiwB3ryKm69QyrXgP25AygWbT+X2Y7GaUhaC+cx27ZDTdc50knxGMAL+ng5Cpuo5kJfvlpyvoM0VZj3+4sbuYxts3Xs7UP7yHQyZaONSOykyZ76nqeo1ztMNCPM589n/wX9ndpfneVScTzrjx22PBegUwK9lgqHIjrafRjV29/dk105bOvFJzT3WlC0+y2dRGxESvNlXE3ayIahyjyLjs8D6rbWHZLTbYcSuVa3yUdo74yOfXaI1bson3K3FbhO1WuM1IvBjC/7xroaOzuvwVDxCEe6uTk4sBxIWKU5erc9Hvhe4XtVN017RVj39nKPOz2/DPBy7nibRh9WispkGPaK7UjaNck1t/U+oldRjIgHu0YDYXHXhGO37po22ZZWUNnkv9FLNop870a19MpxCmwXcqcFgkAQ8IGnskIEsAEegrM13aIdjBNtmNC6Y+AXqmt0smFuR1eayXrwGhsP5SUzlqemL3SewRWUMzzZkHcY7FQC2WXJmCvrL8deQyR7LBTdvYKSRsNj3e+uyvT6uB0jRHf4E7sleUzCLl+zDx+ywUkn6u5aRaKf2Xc3Jt77s1WySk/sMx9KvKjIlW5h6TfwTZR6JwZPJ8yLZeQxcJazlD7rCQ7O8VKsLNUyMkgZqcICUifXLFtFiFXCguxt1TWpMROsQEObOqb27npG6Giy5mlMBczx0IpnNckgvtpRaX/BuJ8kPsA2MBeqW1hNLFEjjohBIDN8dJVOn5DpRD7/KRYlzfus1iM86lE2YbQ8NY/HZLftlR235e8LoDnPBTL9sQHIQ27xQfzwx4X26KOW7ZVOrBbDgN5Leh5hFe9sECa3W5SjrfDs3W4wBxJ651mWBj2GTJStjDzSGsLusC9s8LlXpVToAu5QEwST5iu+AXY6+vddgCHU41zIG4D3Ib3ENlhZ93EQKcmhfnW5riCPhzyALwdnbmq+VZtlYx25jIyD+QH2wisYKpyVr5g+or2ytHrUZr/XTuNkO60ah49wwXyeqpd0y1TKNBDMKejVkBVuQPoybFCnfjV+vsK5jDEbYDb4Pap8g3S27RZmkCn3zXMnbu6BeyubJLU9C1slVI1XjMabJf6ijznqEq0V0pUOUthJwC22pVGC5uGXbn6t4M4CR/EOW2macyRKibQfTCHrcapkl6Bnig5iSo3/e+teLsj0wdxF8A5lgpNQ6FOFboNYxvmRwHbtWqr1VvD3qgUXjXesa0CHOyRn3KHZQVVvms392TV0F45BPwr4KXxW03bp+OEICDeVocMwlyrcUlVObCDui5fhs70oekL3LcOTo+1AhPiGuAb0NM2zLxT3no6VdrtgV2l/FJbJXYTUCy9Mw1zWs04GPDnd3bquBdVXsNeCZVR247xqXEOxK12cPjlHzsuF9tksQcGAnUK7i3Dzl5ZAc8JAm4D2suCCO2VWxAfHSrcBXCOIneOTjF8cTfMW6vyYMtrQDFTBDzUuD/agLzItCytG32p8kpRW4HnluWCeIo6p2vMde7T6lzMBOYzIAasoDagnXKQrZ6JfQYCqBqn4B4G6YQ4VeGu0SoxVW6rcJ3HhnlKVFftRx/D96LGQ9FoneY/ayWzPcHlSLwcLtkeznbY0+z9KtB2Y57nuzcNo/xqEVppETVuQ5z0B6pp9nfXZ96+r/klIGbyXcp1Gjxpdm2QUCuQtsMVFOa26l6m2wB3QVwIiXGYLYtFfcbFfvF9APOmH1PhmycF27bh2De1b/Zh++McW4V70rfn7X7XXciqarxUJGVEP9ZKzWCq8mKVW0uV515FHBEBiNPfu+/wr1tJv4gNbsvP1WqREG5bRRK7hUyzw0jjPHGTM5Ghxi1LBdhBfLDgS4v3QdZ1673LVrGVOe0APTVaqtsWKqY3Nd4wgiAvAl0AcsFyW3rlORaL9TvUdq9XTr7H/PQU/35NWwh9V33Om318ECdJd2W5yrZnE6DvYD4Lt61CYU7aFRq4sj6+lkpjsdW9wdyE+DjMTohTgFN4u0A+L4Cmv22gu2BurDeHdVJ8vl/K0+VyyroJNZ6wUg5T4yUnq8jy3JYiT9lrmWmLOz5DqtwD8+Q6loi21QZ8TniUrTedDXdHGXZ+ac8TG5DpjTnKI186+mYAA9bOzfWjl5Wob11fdLMS5b39puqbQpsC3QS4DW7XLfc2xO3b7ynM7bKqdmSu4I4lZKRjlhFNG/QsI3WkhHPfbuDbnhBlIC+QA1mq3FcWPKo812KJ1B/q+ORAlK3KS+VWqWXjgLML2C6bJQp26xg3gK5n6w7PWUIOYoW34ZPrVU/mRRdvPVlsCyAWSFM1PgiJYZidELc9bh1ONU5XhQVx100+LlUeG19Ow+1px1ZKJPTJMUWNR8qy8+7mOfNmqvFaYC45sQWiyOJFa0Vey0M2yoRzhZXCPJqvpcWS0C4b8hzoVx9z7gJ2AOrGdFKG3jUoxO3VpWEOCaXK9Xyh5q0Z1o8I00T74kIatopW48Og4K07N0MQpyNWAKalohefgNoE9l6Vl0RQzftslUw13q2l4qnzUDXeeCTDqdZKtipPhXluW1JgXnLSqqnKi01TqziOyvZAPKTKAXNbUVVuWitY6KdUua3GbUtF0gIDFZp2ivVoWWAZlSINiI8OgBsgjyykocAdqtulyu3vNSJZnTPVeHpDAtZLDsQTIgvijdR4jSgHeQwclQFXrRyOxZJcz7asp6hyVxpP2dnL6gF7TJmHOk+lEE5VLualnYsixyy3pygSNU49ciEJqOyTsP6/QnxT51qNr9C2xo/bKnwQcgV36OafYZk1Y6/AfQ/FSlHlxrnSsDj2+UPTstR4SQdnC188QY1XKZudN7wta1wtn97ZmQ2URhZL1C+PWSy5MHfMT1blmTZS8jbgKHMXwL2XuJLQW3sdy2eAuiEI6rsyisWWfgE69cm9dRkwV3UqH9yC9qLCx8ViGcQ2ZlwDnDOem970M5BtG7JTKl9QAfBAmSuubDXuOuZKIR5b4N4tlZPVOMAAeRV/NaLKD7NYjoK5rywPzIPti9UZKIfWHetgLQkT3PS7rpzM88TWtGX8ODZVTmFuAJt65FY9khRs7HoE5uuLlRc1bo9QCUHcZa34wrBSIE2Yw62UQ8Ht6HQpdNd8rxq3IW5UFJnmg/guT+x3BxDPnQfwT5jBMuJJ6ijyFjKCW36PMLdOXOxRKnS+A8ah4ICdsxzcbelqk2m1bDS1bZZgeUQtb7dbYh16KBa/fJ0nyXSB9UmIQkpTKQpSkeGJwxhuqH3xgUD8MswGwF1DDjlBoe2yT3I7Om3QmgB3ZciEy7odY+V7vtt13zrEK0QNWwU40lopUeXAfcHckT803wfpoFceU+Wc5YuFdLRZmnZKzDs36l4mr8sklg7O2ZFWPU3K8NCNm4QCoceq0+ep6KGG1FKhEKdwB7aOzcFq3Ly8V87liau6JQap5tNIhbidNgzzCmrcdXwZwHaku3eIH6HGmVEP5BwIvHGYO/O4YO6Yz4W5UWaCEvete9YVgeeAotD2At0uQ5C2aU9c6BlbGm2xCIltiCKpy6kUV6UvV1uFdnBSS0VDfBQbwC8LtIdlmjv0GMlhbat9AxANjr0ipXDeor9bhfa+Kx3fKeBhTmNB3NUZyoLuA+J21FLjABPkVXxyZtwzzLM7P+1yA+vAlWanymHNI7+3cgT0o2U5ob1x12vgdh464CGtbvuitLUHvjaQrMcFxBDCGGeuv9th357vuvHHBfGLVuKQK8B5tgoBujABrlW5PT0WvlEntvr2jl5ZIeyapn/764pC3KfG3xrEawazrrrWSgVVDjxgvoNxZL1yLBbndzjajP305LDgrUNNk9t3V11iSSMAYwTLmlCYt/EvwNedoqsal47VtqpxYqksnrj2xi8WxC9iNgBuWyvA3iZZp5P93L5FPzeUOhd7/knA540HLZVohfr/A+Ks+cDhahw4a/jhPcEcJF0CzPWkVJjnWiwSW1ucXjngXZ86fSydKzalDhPitkJfKyNtX60QYSQQBPBCSGAWJsAD7dtOAvr2+62DU6txCvHLMBkjVlxqfADxt4V9N6e6TPDB3hUzUdUxyyXmjVexVLgQD4E5BHHuie1OIN4i2CBn2yscVQ6cCnM9e5eeJvBMMyDsqsvKs4M5KcSAr85TCeYruO3yXCvBo8rVMEC5a9davpWXEwbYSX5qydAbhFagky2mYawtFikBaFWOrfzdqBWtyAftjWMdmTIKiadxWuC9QVx3diqYqwpGsvGndR8etuUR6ZbJ7FDauoxZbtDmqnGfpVIV4hwVHkrnSuuKGgAP5InO48wH2BBnq/GEY+vcG4JOgjlAQMTJw1Xnnt87+Meslhowt/OC5NNFVQBzVKUTNW6qc70q5C7vCnWtxnUFUk0cIDETi0XMEmIW6zBE5ZPTFTXrglX6pdhhmFdvXMNbw/x5vK4dnINYxpQ7FlJ1VgpsT1EZHDvXjFmOztWTa7NosNu2CYX4+lJq+MCuf8NMUwviIRVup/XFnUG8VTR61Rv4QDgC5nDPT4a5VU5T39yGbyrMXXlp+x3wNiC/Jleq3K7eeWJzTA+F8SYgV14BdUukWCoYdCJ1g80wCcwCEBMgBqxvENKf3bYQIP64VuGbGh8XmD+P11WRa4BTRa5DDzXUK2VKOJhnCCfEta2y/cdOjfs6OHe+uAVxCTpNJ4SRxgtxH6BbQTwgDFyRfbfmwRCv7Y3rSAI5214BzoE5AnV62kP5ySrPAU3AArGrYFsl60whmJPvVWC+lEfVOLVSktS4VQ4726rKCcSpOqehYaSBTlbmAIFZKCWuOjvVd/oqOVebIbBaK+tIlcUXfx4mA+JPayfnbNgpW7hUuOp1TVXaLsskFlp9e31xdADxW1Xh7DSNIJ64MzR+jC2qw1wnzaqzpjp3KVKmOjeWgxDVnE7yh2BuJQvCnCwoVdamL56oyncnBrEH8tog8/v2Tk5JIGJmEVCKXFsmclxGiWglLoga15/1ZGHVT/zxtZNTyAXgk/LExYx3C8yfhmkddmjHLAfLVlEwn5a1pu0f52qwwLt54Xw1bkN8+60LFlGI+wBupnMAupUKd+XxTcPJKhxoB/GMSAZ5kioHqsOc1YYj1LljWnV17qDrWgfc82x17YK0C+a00CjMXeo+8H0HZ6fyJuXa8/W4cqkWUkESGKBWlByW18GNFsTpcontBctaiT+N0/p5Hq54Hia8G694Hq6LGl9GtcAE+YQBg5gUgOWwwhtQHaH2zTvr3Z4WtA2A09VRCeJrmRTicqtjXfd2GivfQ4W70jWEeAb0j+nsPAPmsXoj6pwmCebxAL2JOid1pVgtdJoP5gZ4YU13rBhnOR5we0NuUNcdout3SsNhKVcshV8XmAtATALDICFHATFLNRTRsGtIfUK/CQirGn8a3BC/DBNG7G8AUvDWnacDZqlHsfg7NO3QSt2nxtfVE4D4lqYBxI9U4UcAnDOfmwZoC/HMyAJ5sioH0mGuK4q0gyb31otA3blAt9M71LbRtkbq3BqZtyXhwHxf5K5pxnlCOCwWWt7yHfqu0PV3BPJkmpjkbmgiZqWmpZDAuBWqR5HIQUBMwDABclKcpTDXCyXIDUAXrcSXj4b4u+GKJ6GGHWqQY22GwCiASQy4zkplD8INcA3rWYq1Y5PCmn40qG1LJUmJr9NMiDv9cAewdxA3wE2/V1LhvuPRMf0WAQ5kQjwT/McOP0yBOZCkznXyYN0I1J8KdF96axlTgJ6jzin76TyjePvkopM5FPh6goA5fYO2CfPdVQJ0/Yreax3rgG+4ffRleKLRGWqtJ4EFXqP6r4cgDgMgJwk5iW08uYSlxtVHg/xpmIkaV58P4yuexKQ+wwRgu4NzxgJxqZ6pOwulzGeYEKcjVxSoN1tFEqhTUJuQJ+BGJsR3ChvtVHgqwF15PNO6AThwDMQLIhvkWaocyIO5rpDRJprFWz8CbagBdMc0FtBt4PqAThvkUuf2dGsB9DSfAvd9l0unIoX5Cth13jZNw3M9SS0f7/ZZ7JR1RIui9Rb6OSoSwCAxLDfhyAEYrgLzCAyTxDzrV8ItJw+h1qNW5JdR+ePvR2WpfBhf8WF8XdX4k5jUw7LIBpwhFMQXBR56WiFV28ZvD8Q3L3yD9USmU4iv5zcCcW+nJlXh2H57IZ4C8FA6X7wBgAMFEC+Af5EiL4I5cJ9A9yVwQdqux0ofArrPUtm1y55uwdyuWi7gFfZ0eGA+QKlgMo9aLBBSPQNlJr8J1H1wWCEuidUyq/UghIAcBWbMGDAohT4AwxWYJ4FhAuYZO0Wu7+J80lbKeDUg/nF42SBORqrMclgXTkN8sto9L7fhb//V96scnJbKRFT4NA9siMf88CwV7lLYLS0UzzH3ZgEOFEEcqGCtZMMcSFfnQDugw9OWVKD78ljTSi0XuSRIBTpV57bVQtWyLe6NafrhVLMD5gIE3IAcxPYoWuMj1NhwufjpdkM1xGdprEehF1oKDBgUzIcBchCQIyCmJa/+6EYPSpFrW+V5mPDegvj7QVkruxt/1o02YIDEZK3XyYKzrcCneTC/eyA+zYPXTrGtFJYKv3eAc9nRGODAuRAHKnnkxTAHDgE6zZbclgDwXbz2lncy0HfTdLnLNnSCW6t0ie2VawDEoIAhZgLz5bVs+tEjxqNoNcBtVb6CHcZoFcMvn6WxycWw3JJPzkZyHDBcBYbrcqMQPQEI5Y8/X5Qaf395xXeXF3y6fMP341e8G17xXlzVzT+LnzNhUGpczBi0tbLELMU636fGKdCv87BCXCtuDfF5mU4hPs/7USoU4rcO8K7UN3AOwIEqEAcqdnYWwRwoB7puRCSqqnTHfKcaZtguu5ONnacW0BcKG9MoIPVPDXYNU92MgYBjtVQ0POSWlsB8f+mlG6FUuZjJycS1CWetzOXW5nlR+nLAIATkKDG8SgxPEmISqzJXJ6JFjY/qmSrvLld8Gl/wYXjBx+XzblHjdMz4AIlXABMZlUJHoBiqWwpcpRrNcp3H9fuk/xOIT/OwgNy0XFJVuNdGqQ3wI9R3DXinpAOy4Q1UADhQDeJA5VErxTAH8oEOtFXpvjZ52ttMpbcAut5uPnUuCLwl1mejyMGcttoow1K8sU4smEssoBeLVSOhbvxZ3t6zKPx1WRbPXHWEykXZC2MdyVGp8eGqfPLVIRFYbZV3lys+Lkr8u0WNfxy+4f3wigHqVvxJCszLnZozBF6XkSl6SOGEYVXjr/OIV6ngPUvhhfhqv1gQd/nhVI27RqTcGsC7sk6A8wEOVIU40GD4IUvxciIG0GDePJVuZ01qk12NdH7dkpWqdE9TtN8sV0/E3zQO0FdQ07z6jTxEses2SqFgLgUBqbH0cvddjmuDgVFsZQpptF1ZLPMC9FnBfJ4xyBEQAuMgMD8JzE8S12kByLLexGKrfLi84tP4gu/Gb/hu/Irvxq/4NHzDk7hihMQEgREDXqQCto5ZKjC/zuOqul+XzkwN75fp4oX4tKpy00qZ5yGqwosB3hLet6C8gT7gDVQHuI5m48irqHMdtaAORDeoPdu7DJn2SxTqOlFNqGuV7klrAH357wU6hTedBjINxGpZ8kuhRbQgw/pUwTOWaVeVT4Edywsk5DbCRqvyeQak3CwWKaGfXDs8DxielSoX07aQw3ITkFbjf3X5gr8av+CH4cuqxgEoiC//X+Xmk09ywKscyWfAy3zBtwXeGuKvk4L6NGugh1W47YWzAG6BmQ3wW4b3geAGKsNbRyOIA41vCGIr3ZQogbrdkFpqPaDGd/M9UDeS2ekLob5T6YLkI/BepwMm0HVZIaDreUvnpvK9xdZ5KbaPvpFHCLk8L0U/dkoVJCWA5bZ7SAExCAVsIZQSlxKY5pVgYlLKeRQC8mnA/CwwvEI9VGtR9uMo8f5yxfeXb/jV02f81fgZPwxf8P34BU/LOJR5UeIjBnyVW2emCfAR3+bLCvGXecR1HvEyjwreC8x9KnxOBbhe/xbAs9R3ZXjfk2UC3B68aRx2Z2c1y4VGDKDR/GVq3VWEmmhn5M1zgj3xeHMlX0ENKLtihXcA6iCwXipalTcD6OsV2fJyZEGGIGrbRT1PXKrb6yFWmCuFPmzjxCWWIYwLzAGlyDXMxbyq9eEyYHweML6oESz6xHK5TPj09IIfnz7jV5df8OvLz/hh+Ir34nW5zV5BHBgxQXnkr3LEV3nB1/kJn+dnfJsv+DI9GRB/mS94mUal2KfRUOHTLFgAl8vt/jbAs+Gdo7zPBncOF3oEt46DAK7j8DcENVHpa4F2Zan5HRlqWDEVwJ6l1h1NMcplQl1PW0ewkHmL4N1ATlT5DuiLCtdv9pkF1DBBsbRleTyhHrmiYa687kGVM88qI7DAe15GtSiYj5cB8nnA+DJCXFX5GNSLI757Umr81+PP+HH4vHjjk4K4ACDHBeAK3t+WD4W4BvnLpCD+Om1qnKrwad7GjNsAn2fBU9/UOukN3keDuxDaQGNwA4fDm8apr3pj+9G54ZSnqWWkwZ2l2kPt8sxznh/stFR567aQco1RMNJKQ6G+zgio8hDU9W8J9XjZ5VniYgawvpJNKXGhx54Py1MMB6GenbI8e3wY9MOpVHuG5UErYloKnCVwvQJXQFzVA8rHy4DLdxeML8MCcuDD8yv++vkX/PbpL/jt5Sf8s/EXPC29sV8BzPMTXjHi6/yEX+Z3+Dy/w0/Te3yen/HL9R2B+KbCX+fRsFFep8FQ4Bre9igU9QTFRHjb4AadRvYBLngf0C6PE8Ftx7nv7LSiOdgBhkzllOFJ7NkBffulfQu5O7NnHhfudjusE8ZOga91Wmode4iDfidQX2205c7K9bb+YZsmZrG8EEJuMB9VB6WcVGclhAK8Gloo1zYPALnzcwaugLxOwFU9GXwYB1x+ecb47aJOFuOM755e8Jvnn/C3lz/hN+NP+H54BQB8XXzvr1IB/C/zB/w8vcefpw/4+foOX+Zn/Hx9xtfpCS/TBV+niwHw12lcLZRJinUUyvafqG/bNlnXn2WbxFR3BXAnQ/stA1tHR+C2oyuQ28ECYK0I7VPc+kINcyxMEeB91TjUv7B+O1W7DXZalv0kQh/YbbiLLat+cw+1tNUbfZbnh48K6upRtMsDsMbl0bTjgOFVqfVxEOq/2BopFojjeoWcFcwvH5/x9OUJYhoxXCR+9f4z/vnzH/D3lz/h18MLRgF8lQKvclgA/h5/uH6HP08f8efrB/w8vcMv13f4ZXrG16tS4t8mZaW8zgOuC8DXW+5nwYO3S3VzwV0T2kcB+9ZgDXQNbF90DXJfxPaNQywaO2J1xhpFFoq1fL40FqiNpjnsG2H9Nk4E5LsB7WXGCmmtKtfvW1nrMMZh+278p69om4W6I3RenmK43KE5XAWGJ4nxSaoRKc8D5NOgOjYvw9oBKucJ8uUVmCaMz094+usPGF5HjJcJf//+T/iH59/hb8YXPAuBX2aJn+Yn/H76Hr+7fo8/TN/hj9dP+OPrxxXgn6/P+HZVHZuv89KZOQ2rD66V9zwLyHnzvOUsduAOWiVcpe3ZNmobVIT1gaA+HNLATYI6FjcJ8lhw9q3uYM9pkFZyMdDHZlBFbn+hkE8CfBzuGuy009T4T6A+z+ruTMxQz06ZBKarwPgqMTwroI/PS8fmZcAwDqrp0wT59Rvw57/g3R++x/jtGe/fveJfffhv+JeXv+D7YcRP84Q/zM/4x+uP+Kfrj/jd6w/44+tH/On1I366vsPn6zO+XJ/w7XrBdR7wch23oYSzWD9SP+QqBO4YtBOAzYZ1LVA/IH0zcZcg50TJPpq9g+bWuUKWV7HdYRlqx+4xALQcl8VDbRjSNBs+CuAm3FdoL22jo10ozPXveVHnYt7eAHS9Lgr9CowvanTK5dMFl8/PuHx8xvh0Af7yE+aff8H4T3/E81++w/ff/YJ/++E/4TfjBb+frvjP1x/wH19+i//y8mv8/uV7/PeXT/j59R1+eX1Wo1Gulw3e06a4Zyk2aK/2CUxgxzooHetq2xaOjkxfvpR5a5q8HfBhbfQfbxbkJVHB9tsF+9EAJYU66gguS2DmqsR3echXCik6W/8x1PuWQKv51XqhFoxUUNeWi9BA/3bB0xdlp7z7ww8Y/+sfMP/pz/j4+7/Dv/nxv+JfXF7x71+f8O++/Gv8hy9/g3/8+iP++PUjfn59xpeXJ2WbXEdM0+J1L/DWo2wwE3/bB2mHReKFc47tkbjjvbWRG285HiDvJFqcHHbBrGNT6f6jNHr8xs4h1gLvqrI6WIX+rn/T0S+zhvuI4XXE5esznn76Dh9/d8XLDyP+y+cf8b/9t/8Z//ef/g7//edP+PrtCdN1xHwVkNOwPLvc7IjcrhTEVrdrQXa/wyu5Clwf8HyEFZdstfeIuw3y2O38MmL71f6JWuaJRpj/pSBE1/MGqb6P6jG14jLj8jRBvHvFj58+49/8+E/4/z7/Cv/0f/4D/vDThM+/uUB8L/D8DpifAHnBMl5dPc8Fw9JuUsfKTKs93mWMkbrC8XbISf8RNxUPRd5LHHBwJgMgBKXQqBnPbwPGdlob1GKB9KDuBBXLG37UezdnjKPE5TLhaZzw4fkV3z294FfvP+Pv3/8J/+rDf8O//fCf8C8ur/hf/+l/wV/+/C/w4f/6f/Hpx7/C9Le/wrdfv8PLDyOu7wdM74DpWSiwjwTuYjmhabivkJcb7Jf2SmN5xP4kEFkvNILbaFlHbFXf4z71iCbxAHlOHLzzZh8snCM+CI74NEnrcAGatoPO16Bevq+36S8qWwwSg9hemDyOM8blCYbPlwnvL1d8enrBd0/f8NfPv+A3zz/hnz//Af/w/Dv8y8tf8Jvxgn//+oT/589/g8+/veDTX/2A6Xe/x/D5Mz7+jx/w7lefcP3+Ha6fRlw/DJiexQr0+QL1TtAR6/tAoe82XR4jIAdsEBf0u9xuiNpdVfjX067P2bnu/RvLuY/Ymz/X1wnsIy18+MfJIT3eLshP2FmKd1DuURO1NXjTnJD25vfAev0OA9jqmSobtAUAMcwYFnAPy4sgxmHG82Va3+zz4fKKj5cXfH/5ph6A9fQZv336C/728if8/eVP+JvxBd8PI34/XfHvvvxr/P7nTxi/F5j+7tcYvnyB/OWzGmf+8orh80dcPr3D9OkJ1/cjpvfDAnOBaQU6MF8EMADziA3owx7m6r9wAx5qeb0wt9evYzTR7mYvMp93l7Cg/+JhPPoyIzL395KTw1s9CdwnyO8Z0kAeqD3TpV0vF9h0vgvaS1onuJfvgijuYZghBFZ4X0b1tvunYca78Yp3lyvej6/4/vINn5ZH0f7q8gt+Pf6M315+wm/Gn/DrQd3s89M84T9ff8B/+PI3+PbtCc/vgW+/foeP/+MHNc58moEvX5RzM80Q1xni5Qnjy4jr+3G56UhgvuiPVM99GYF5JFAXBOjUjoFaRg3z7btY3RdJ1pHUboxLqZPvwrVtXKwNDCkNTN7XWXpDBmeXrnysJtyOcVdxmyC/FWuDRk1Qh9JwYG2n85Yl9/NtaFvTfOCGUFYJhAK3ehnyosCFVt8SlwXeT6N6SfLzMOH98lafD+Mrfrh8WV4K8Rm/vqinGP6z8Rd8P7xiFMAvs8Qf5mf8x5ff4h+//ojr64jLE/D6/YjpV58wvrwCX76otxh9e1lGpEiM1xnD9Qnidcb8bsTwbljeNrTAfFHmw6igLkao58C4FDr5T20WoyN1XXdiBbQN93UVRwBPbHlzW/kEtURgm8d3VaPu0tusO4T9LYK+b5AfuEIPhzVQHdhARGEHywt43Uxwq9971a2VOVXew6DejzksAH8aJ4xCLip8wvvxiudRqfDvLupFyd9dvuGvxi/4bvyKH8df8MOgX9O2PMVQCvw0P+Efrz/iv7z8Gn/8+hFyEpAj8PphwPX7dxg+f1TOxbcX1eBpgni9qgYPwCjVw8LELDFN6pnm0/MAcVE3JM0XpcoVyOXqoctBrDAXpINUP7JX/97Wn/ndUOX6kQPW+qe2jHEjl6Qqer+dhfUb8Ng0oaDlefK6ffrATs49XlrcYxEqMmX5Oom+QH7Airo5YAfmRZV2qNxYJ6XHKgEcqntJZyvv9S1Ag1z/D8v8YZjxtHRgUoA/jxOeB6XEP4yv+DC+4tPlGz4OL/h+ecfmD8MXfBq+4b1Qb74H9FMMB/x++h7/dP0Rv3/5Hj+/PkNOA+QITO+A68cRl0/vlJ0CAJPKi2lWD976phZ0AJZeTmCexDpefb6o/2JR5fOong2jAK6hLjY1bil0MZu/d+ueQl+v5+WL1PAmd2LRB57t7tCVEYa6rtzWP3Ziz3RaHzIAyHpqXCQY7aoVu/vrOgL7uSBvvCIe0KbzIh2XvqGB2ufWaTzwVkLStE4MiBP7RPvg4zLteVDDCJ+H6wpyDfF3w3V50/0LPg7fFMCHVzxhWt/s8xXAqxzxy/wOv7t+j9+9/oD//vIJX16e1mehT88C148Dpk9PENflnZ+vV/XKuEFAv6RCXGdATOvzz8Vieot5gJjU+HP9LBgxS3X7vlbl8wL0AcAgluesQ92VSseoSxhWywZpsu7JCVTq9QysX2ywG4pcnwhomRGwk6KNcMJd2AkC83U77HJDbXHNTD0OGe0qjZ7AfjzIGy7sPYEbOBfeAFHeyzzb89ZZdKelfvuPDXCtwFeIC4nL4oOPYl7hfRlmfBhfV5C/G674OLzg3fCKd8OrAri4ri9K1m/2mecnfJVP6lG003f44+tH/Pz6Dq/TqG6xHyTkRQ0vvL4fVcfmdQaEUEpcyo1iUgKTBK7zspwCg5Dra+d0EvVfnQCkVEp81i+NloBcpkMqD1xqqA7YYKt/a6DT1U9Ab/yW5jRIS62DJ1J3aWzVLYx/Zp4YJEPg15NSIWgnyBnawmhXSdAmHQ3140DeYMEOHSkC8JfhLHADbngLx/wUeK/fsVPfmxfuB/gg4FTh+v9lmPA86M5NE+Lvh1e8F1c8iQkDZozL0ahflAw54hVKjf/hqh5F+6fXj/jl9RnX67i8T05529OzwPRePWhruD5hXeB53r4D6mFfUqq3D02Lp0/eIareKSrVM9OxvL5tlBjkos4lsD1ES67A3QGdgFmv31Wl683gVOV8qPuUuD0peiSISJ4U1c4U3Ier9oqMWlf/QUBvC/K3Au8oXN2TneB2pc+BN/3OgbeVTqvvdT4T4EJIjPr/oP9vKnwcZlyEUuMXMeN5vOIi5hXi7wYFbfoZxIwRqowJAiO2FyXPGPB1fsJf5g/48/QRf1weRfv1esE0LTbE8to4DfPr+xHidcYopeqQXKwWvbBSE3eBuZiVSheDUL8ntZLUi6IBSA109eLoDeKLOh+glPuwPAiMqnKqyNeTJZlGN43Y9v8N3uYxsX5doK6mhZW64bGDnCRooRG1vivfkd6d0DFfT05VuMaKKFTsldh1lEpvB/KKjS5aAWeo7sD8w+BN03AAvkI7DeD6+zCoDsSQCr8MM0ah/rsg/iRmA+CjmFeIA8AkF4gDGDFggsCrvOCX+Z16Pdv1A35Znif+ch0xz8PWMbiAfH4SmJ8F5nejeiMRAIhJgVpKBfFhWzlCaoWtgU5ge9Uw3+TxgMVqkWI9F0DDG3rdCgPUO3i7gL5U4bRZlqLpNLq55fJNEFLVhrr1lQ91znzsD+PmVkwjqLeCeX2QV2rozcE7MI9lmXDakQNv+j0X4EvavfpGUIUPy/QQxC+DUuZP+vsw42nYIE5D2ykjBnyVYlXjn+d36h2b0zv8dH2HL9cnXKdxfXa4Bp+8qDs2x6dlSOE8Alhe7KxV+eKXS6vnT2ibRPWFLitJAtM2DtygqGOw9k6dkxOsAe/t/LNC2gt0Mp/WbNS7ThdkWgOok8pYULcT2vMDx8Ohar0i1FtZLnVBXqFxhwG8F+XNquN4gG/z/CqceuEuK2XwQPwyTBiExGWYlAofiH2yqO+BHD0TBvVbqu+v6/8R3+Yn/DS9x89X9Y7Nr5N6s8+0PFNcrwe53I05X4DpSd25ORHFLgSUJ248RF2Y++MMZcVIQEolr/TLo1eSGuceE+brWPFB1SUHsQ5JNOCtp2lwi42ZtiI34M0Eupqn14004ULPINLMuIOQNd83zQt1XxmuxC2gXmK/VAB6TZjXA3lho5o+GMpIXyHN0erbTl8C8GX+rhNzmb+qcLENO/R54QJ7K0Wr8xDE9XedbgDpHF1+05jlgFdgsTAUxGc54Ku84Nv8hM/zM77Mz/hlel5fzzZNAzALCLloz8Un189OmZ8EhqtQ7wWVy50706w8cAqswdpQi1Uilv/6JdIQUnWs7pQ4+b0MURTrNpLLSUbs4C2GLaeG9HpzkZ5OYOuCtw/oVGknAd3Oy63UAXUv0K307Pl6VoriraHSC7hXE+Z1QF7QmEMAXkN9p8Lbl6djgKs8cRWuIa7BHYK4CemZgHve/i9qfLCWfZYDZihSTsvoFD39VY6LrfKMX67v8PNVve3+23RZ/HGxDhgBFmtlwPrslPmi7BV9QA56+Wa5v+tROPbTWW40XaBujFSxpq8ukYb5Mr5cDkudQpjwnjdwr4Anm9mlztddwAJENaDD/O1UwjVVup0wUJ4dh6n0QqDXgnk5yI+GeG2A11bfvjwnA1xN39soerYGuJ4XgvgoNlVOIa6Brf3xAeZ3qrpH8t+OGWIZ/aHGbQ9kYWc5YFpA/nl+xrf5gi/TE75OT3iZR7zqN9wvr2kzRofoh1uNymYZRtX5KeZtaCEmJbN3IFg7QXfNVcMVZ7EdlTbYFxtlBfqA7SSjYQ4JOS9DFAdTCFOdv07TENfTKUh1U+x2kiT2jBKgr+2x20HT+6aF2hXIs8tQW6XnAP1EmJeBPLPyuwR4DryBdIDT6T6A62kU4Et6jgrXZaVCfLVKxOabD0Lisqhulxq3Y5YCowAmJVWBBdyAAryGuPLHFcS/TE94mS74Nl3wOqmXJs8aqEusilwD/CIwT1BwnbZx4mJQvrfu2FxDP4vc3i5rBfZHHZ0a3Pr3apOsAIcJcwhjngvmVHFH1TlgAtKAthXkXESBVgXovgZxrhwc9STPd7UtFDlAL1DnpTDPB/lREH8AfD/dMZ+twpc0qwrXv4kK1/liEBcE1hriqzInChyAAXhf2BCf5bj65doff53HFeQrxOcRXxeIX8lb71d1vFx96KGF86ieYqifnTIv9wYNGJabgKAg7tgmK8xt79zeJMtnhd/yWUG8/F+LlrqpcZi7vuvivOqcZoBjuusEUBPotIGwpsGcfhdAPxjmh96i3wzivQCcVU8BwOl3nwpf0lAVvqazrZQlDwfigkzXEF+VN7Z8GuL6O4BVjetw2SnTYh5PQv2f5YhBSCyPtcIsBSYMuM7DqsZfyOeV2Crz+iLlrfz1jknDXlEPwBKzFuDLS5yFUunCKmODuS5vv7HXsejAqsJXFSwVpHdAX75vTF1gLmEzdgO1NKdTO8UEsdF09ZPAe6fOXfNaKPRbBPoBMM+NPJBnNDAJ4j0D3JcnVYXb6Wur8OW3nWaF+M5C2fK5IL6p7Q3YxsgVh6VClTlgDimkMcsBw/IUw+s8YF6ebzJJPV8QkKunHL7Mykp5mUa8TOOixscV5OsYcrIe6XPDZ/1M8REr+IeVYGrFSO2Vz6SgwRqSGALJCvBNgYtFpm+/N2uEQltAQkphWCpeBW41R8PaUHhUndttDajzfTkb0HbluxqnJ6cA3ZrWDdBT1XkGzHNV+SGKvEuInwVwO0+GCgfOgbgOCmtY832wdsW8PBpwEFJ52mJ5YLec1e8l1HBDsYxWIRCfx1WNT1JgWkaqyJm80cELc/UwrXkUy0gVsQwTl8B1IRm1ZmiQJxCq/yLtgLWhaitsi1wuvtI0Rj7rtxfmdqH2dOznrcvsU+ekDtp+G+g7u8VK44NvMdAj24gN0RR1fpAyTwd5YqNOgXjm/EMBbv9OVeE0D4X4+n1Ls371QBxkvg/iVI3TZtoe+P77vkNzksKwWvQIlVmq9PMyzHCdL9WDql7nEVc5mBBf1PjayTmrU4l+8iD0P0H+E3tFzlqRSwwgMJ/ENhTRtRO7thEA+45QNRE7cPu+A9tvbbHoWS5lvrNZ7N80HbaJNK8f2PsKs9W5tXxrHfDk8U1zFGtECJxMdX42zHNUeVNFXh3iLHjmzetWhZM0HBVup+NA3OeJuyAeUuNGWxyhnxqov6uvSpVPEBiFxCxNiE+LEp+lwKtU1sp1+f8yjXghanyWwuzoJEFhTi0W/UAt+lyUGWoYoJjVBxJqiKEVdBSL8bIIILiPUB/dp8q3/4Uwt7+vjQ8AkQLbVtg72G90Dqpzx28nsFzQ84CQroddep3ANz8Cc4DBr46UeRrIExpyOMQz5ycBnFVPoQr3pCmGOLb5NnhtZc4JDfrUUJaJftsCCMwB6/72FeBq2KFYIf6yKPJJqs5NrcQNb9zVNKEbDsNe0d/nUS5j1m0Jim1Mul0eNohriyXH47RVOStsde0ohwLZBXMntH3TYX5vqs5dMMd++unqvBHMU1V5E0XeFcR7UeH27xjELfga03IgvrNRNoiDpE1R4zRct9bHYlpGdOhsthrXAJ/lgOsC9ZfpgusC8NdJqfHXaVDp5mF56qAD5lqN26pc2ysj1PPE1weGL+RbbyqSHlroshPp7QIrnQ7636PKxT6PC5jVYG43AEyYw8zj+s3yzl3lWM3aRQV1fgvK/ORXvb0RiO+A3hbiW949xO3OTZ3Xhjo3fGDXoTs0twzYqXBtq+iYliOHKvLrvNkqr4ulcjXU+LA+PlZBXMtlfZAt/3XH5Apzpcohl9+SNFQ/bFyXt67Ora32TUKmHy/W397IPbAd8N689T18KZB8kI3CHPt5u/IsmOtJzmWNwdyVxzeNNMsZMXV+JMwbBB/kzJ2NrcZPgnh1gAN+MNu/fbD3pMmFuDDS2Iob3t86r63GAdNG0WmyrRXjiFvu2pT7dDPEOvRw88aHVZErb1zBXr1yU2ydkx5Fvipz+oZ7/UTD0fTxt4xyLU8d1PsdQwqrnoQwALyUoQrdJu5UeUi92sqbAhnkew2Yu8qjZww48rqWEUaWczpCj4I58+SdYq+co8jvBeKN/HCgDOJ2eS5f3EgWUeN0aGIqvLdnpiyPpxVygzkUsCk49R2cGuB62KGG+GRBfOvkHFaAO/ol15DCBLh+UbIksJaGnAU5MchtssV6mnRZWaY6TwkC4uDBbAMbZnrDL6fwcMHZNZ0DcyufsQ64VosDys3UeS8wrxxVQc7aYR8Qj6bxQTzapDW/o6zd97AaLwk6BtwYZujZQWZrASnAtSrXEFcWy7BCXN8ApNS49sfFop4dC6hnL0CXA9RTB7WCX08EBAXrPAJ03zaxxpjTuqM2CyfILhFT5a7vO0hz6kuAuVEHwIe54/ddw5y7/pnBA3nFCovremsQp8kSffHdNOzVt0+NU1uFE1plD9Ksb7NS3CNTXOXMS1rdwTlLsULcsFRWW0VY/vi+3PW4sdS4fqaJgrQaQmf45KtHvqRdCOrbpajFsv4WdhqRpdSN2//JghlQt367wJvklyMy7wHzpsGtq5oir6LG7xnijPKcEF+hHYa40QxiqezK9v32NY+xDLMUO8tFq2/bSvEBXcPbtlameVg7O01fHCvE52XcuOmPu4/q1VrRv/VISAJ488hfypul+dJkncZePRTg9m/PPhc7dgyLxJ7OhaKlrOk0tsXiy8NRl28N5ger8uM88rcOcZ8a15MCbeJC3GWpxLxxGsn+txTLe4qJAocwVLmG/Pp/BfXoKtLwxtVt83uIy8UTX28AktuQw5A/rmO1VRa4btaKUuXrgJollGpf5kkCVoC1X9ID3ns7f+oBHYGdU3W7FHMOzD112u3al/mAeauoAvLmlxn3CnGHck71xddsDktlm+dIx/ztC58K19P0s0u4oRU8Bbihysl33cEppWmrbP64JihdMA1wibUjUlsrGuhiATbkdpBqqBtqfyN5aHXtVbnYz3OlTw2OEg+lT60ncEKwyw/B7h5gXhyVyo+DvMZClKjxW4N4qPwQ7D3TkiwVmGl8ajz13pVYrA+cIjbKgOXpfXpaJHQaH8SppSK1aifDDdfOSsA4WoV1oKwuD4XsAmwpt/Trs8D1C5dnyjEB/Rb64J5tK/FlGgV8FryZ4KmuymNt4MDcUqm3DvMjVDnHJz/3hiAg/0RxFsRjZeR2bjrKtCEejYga92ZjFq+D7tdUhVMbRScY9CIEgC61Godlq2iYW5bKRNT4vKhzQzHrRvoWVGyf1RPXCzUsCRaLhcJ8TUfrEoDrOSzrsrluGKJtCX2vFSWqPNViqQHzSPtPgXkgjuz89EUxyKMLUHI2qrVyciHOLWudVwBxBrQ53jiY03KHGLrADcBQ3y5PfPBURzs39X9JAE4tFGqpmDf/iPVkYIxasawV/V+fZ6ilskJ8VeRifcGy9tBNVQ4COOEhA4ztubdaHPOsPLFwqm697CHg2tNC6tsOuhJidTNh7iw/EKUwT46ScmKqvEIbT75Fv+48rxrPjRJfvKQeZKjxNV9+M1yhAb37Tpqmoe2C+dawfdl0PgU4AAPi2heXUiwWtbA+uq204Y6FscBJmQLrQ/3y9fle1FNfbBhJynbtAjvYMJW5F/I1IhUcqRYLu9xtpaVaLM48CZGlyksslsbRFuQtemxTIZ6rxhv74iFLxVlkTI0H1nXpDT52+OwUDXPAem+xw1ahv9c8Gt6AAXHti+sHY2k1vvY5GnaHCB9RAmpdkWeuGJ9hO8DF8t7OdYgiNivGVuUAUbauOkHSWNNz1TgngoDx2CZJqtxXF0eVx9rKgDmnXUdZLOF2RVR5YRSBvOgMlKvGS+vIgXisDJ+l4sseUfK5ajxYT2CaL9SLHvR3U3UD2/5uK3AKdJ83Lsk0DXBdpg1x140/UgrrTUDCtFUCIRfFTUFqDEckYJfD8oIJAnPdzhV6pGwvM2PKOzItyUdvYTEwVTnnJNCTX54crVR5YfvO7+xMiRQ1XvOMGjzpBMgRATa3jtDdnq50JQqcgjo0bQU7NpgDe/VtDcle89rfKcC3/zA6Pc3hhrptMOwVHbvb8/WyCAJjDW5pwZ1CHYAUapQK7RgVy/8cVb6ms+c5mlz7cj3UaelMF4oYfDyqfJ8uoFYZgGMD1HUVgQNVecMIg7xIcTMBx52XAvGcetc0B1oqzE5KXzUcW4UTTgETgrflha9WBPbPWXGpccNWIb9dEJ/WV7ftx4sbtor9PbScggBdmB+qylcVPgByXmCO7eBf8+eocjuhsNI4oe64simFjcdeCUWSKu/JYvFEMsxzVXmBvRI7Wd2WIueGa4FbnF1reV5HtTcjtL2yg7c0x4jbQFd5ParYmk89cgpxs3MThhpfb/4B4PXFyeahSnwNDXC4bRWdRmIBO/YwX5eXTIjuFZ4Tvg3xENRPiaaWRT7kgBMsls7CdeXLimwlcJYa50SHarz+KBT/PBusG2Bh/d7m2x2VwCaMXR89GoVaJfrGHxvidLz4NuRwU+OGrSJBwB5YASscpRuYyzlhe33b8t/xOjeaRqeDgDqqROAD87txHvJA3B6PnnUcVQznoScj87lpXPNivyPlxcK7yhjLUa0dBe1vo8gb9s7G62ZO26WJtHkH9YOXsXJ9LuskJZ89hhwA6y5Ou5NTT6MnCxvi9Hkqhhp3WSkhmDusA+qNr343/T4A0h5+CPPOTuoc0Kpi4bNackVSMz+9NLgq2FLlqR2f7DRnqvLCKw9f9GOtnK3GmfVG06buIIknntr7nwaz3rdt62QD9zaCxWWr6Omc2FsqMNT5ZqfsLRVbjSME9dByW1bKenxZqnmzVQjM17qxWi0g2ZAKQOvEYk/3qfFm1ksIdDXAyPTKk9qFjPLsvPDsQhle+dFxLMhbL3RvajzBVkmN2mPDXeGCObB55rodnGep0DJ12Co8DHFF26AaXysJNEBD2zHdUOUg6YjIt0W987krGaLLBXA1XeymtYoqCtwH6TemyqtdzTAj2yP3Rg5g7kWNl1R5gD/ui9UTX37Hx32b06lX7ivf9NNNFR6GuHX3JmD4/IY/nrJbCED75D6Lw1C+RLnT/9o3l/QGI90cV9l0vbjSuCDuaFszNZ4Q1fr6U8phpO3FKz8yshT5kWcadrRS4ynpa9gqDWNT2Itd4PDJXRYLgFWZ6+8U5tRy8YUNf/o/DHGdiahxnZeq88wwPHJBlJSlym0v3J6mpi/rxxguwzherPkGwB2Qd5W3A/vRx2iBvbKfl3hJ06kq97cl45ItEge+WKJOMYer8dx2N7RVuBEC9j6tf9y4PZ8CXaXjtEXsvhujXDwQN/6DKnBTmVNVLlbrhQJRrQy9TgxfHCbQ9QG+88cRh7mat00RCWeZnQL3KPXgtF2Z/LTVotResSI6rrxy6O1aXE6OvZK5bOd3dibaKuy0R+y4Leo4zE7ZQ97u+AT2MAewAzq/zj3A9fQQxI3x4na9NrBTQ8iN1jBVuSArIgZzwLHppMceibbJ/9sF5sNh3QCktT3lJuPKfWnPUvYkzgf5mXGmrVIYIZWdOs8Hc2CzWQD36JSQ0rdB7wK4/m/ctbnOx2qp2Gp8Zy4HPEzvlaxNYWFNF9YxSmFPJglzdrrP6svkgnVoeqisUHrGvCZxtL1yx+EHec5KaWwb3IytclKstoFzngvgW3oXzAHs1Dlgvtszpsrt2/Fpvg3ktvViQR7YqfHNO7cXNNgcFS5bRXr+L0XS3zaxjZ9ECRprJgU0VjoWxB1lBzfNje3bOfZKk6GItSLDJw8tT5+K/NZtldQN1PAE5YK7CW0ezIE90NltsOo2//uUOQxLxXyVm0XQgtVnWCiO/0GLxZLjVKkbQM9Ui7vVzIH4wcdDMiwD6+KQIXut7JWT4xiQ+xb8zBVyUKejt6Oz5rI7zu5cC0V998NcLYMJ9NgiuNasC+D6tw1121IxytjB3PrvawBttLS+7+Q3ATXIb1K8XYxdtQvoaxM87fNCjKnQY5ZLqg2THK6VhIMAbdd/dHjqPmrZ648jbxSn2ypnPnaARKwVrmepmOOuhee7O43+7bJQpOdj57PHkSdB3KHGd7ZKjjIX5n/jfOCaJ8g8Yabz5aHpbci6Ps42lkI8B969KE5rpewOwYOR0HP0aa1w4yxbpYc64Vbdvvk+/zykzAHT9kkdpWLnoQA3/zvsFKMQS40v04z/S6zPIXed0JYLl1VR69+2vQKYKtxzKULnG7YKbXehvULb7mrD7rsnTWzTHd7RuVaM462fUnulw0gGefMNfsMr89RI6DyxTwA2zIE90HVwxqPvp+3nGXdrUpWtfwOm+qa/XXZKaRB7xQVwu+NT5XG4CR5IcO0VWp+7neHfSavkcazlRWvoZ5RfT5F3Yj2worO2GmClHWseFR0vz+d5u6e7f6v/ro5Sbhtc+dz2ik7ktlR2ahyw1LlfhUeDqPDdudCCumWjr18owFfGU4VPVxmpK7mdkWk+SyVqtaRGgtI/PG5cWedGe2uFqyzOjDPakrrDEcoYKtA4CZA0TJgD8HZu6vR27OHuaXLAj98PIzQhbhak5y/zqK3iqjsEdApXW1nTkygIrGnRAZiDTFstFbtdrm3usW6Cy2C1yTe/xFOvcrJ5S+HZvt4Oz4Sr6FjchEfevKMzNW5whw355S51rsNlpYReTuHqKLXzBSFO08p9eVsCB+xTg8IccB9xPq/cnr6UZXjlIY/cKovVVkewIX4jUXM4Y3aZNC/ydq2j4yZA7gzGpWa1sns7kVjBUeV2Op8X7hqymNum7ft+OvW6DYi7LBVbjYc2B5ln2yS7YYfYiyIK4p3/vXyhnaM7jljz6TSjTYX7arDzMzb/lmBvbaBqw/lcJ4AbtmVuF+S3GBmXUgaMPfZKqJ64+t7P15Fyo1Kok5POpyp8l8/u3IxWijpHNaU1t2qyKXfgJkX5gA46P6FOZ2RCPFRO8Wq9USDeavQF8sfGV8FUBl6v3E7HgDmQ37Hpqs9Vhg/iO188psZdnZ/ANvSQ00Y4BJkA1Bt/RFSVb+mxV+GW1aLaBucJowiYjrwxpe5Ny23H4xhV0Zl67wvkR0SnNklsTPiW0K/qfRaLmudW3qGOTe6IGfdNSG5rJQTxqC/ubQCQoqbXyFXiJE8U5mQe4PDKU+rnQtmXnqm4uau/W1umM8geEeeA/A2t5OAQQq7yDpSx60OLwByIA91OnxL7zk79RezSuCC+JcJejYN8j9kqrnkeg3Xvi0tjorGOfT77Ms/lj9tpdVO2dvkXIxYsgFvTUlQ7OyqcGB6RH29Pkd9KhCBvAzqQ1EUO34O0dJR647oOuw0GwI3p20RqqewLZTerOLwXPkvz7DtB7ZMB7DTWzCZeObDfEWIQtfeDlLIfsY+Trga6B3l3Qw9Lg2uN7OZZ8I2UA1hA9qhzlc6dPzV2Ct6nwsm8nZ9u/IapxlmNQDC9bY1Ew1bly5cV5nbZlj/uVOe0rSRvdvjypkA6sQ1vCfjkfN1t3MxDs7qKmls1VJYNihCgXNPso00Kt7Ugt09qOPOSeowHY9H5oLaL1VafGvfZKhLb6924oZNrUIvlu266kFHbYs0Da5pVrjGNpheOaQnt9+YNtctOl1JfzrzEeNgwedFWkd/LRgmoXzUfltKKpA9Vxe30dNTj7Edzlec0anV6fludZVp163bZ6ZwQl9Z8DpxrnFRjkouqckcnpq3wXUrc2FQuVd7Qp+ZAvJoaj0Wy9dO7FuZF68fZdm+t3EOk2CL7zDBVYKQsJyt8HZp0z8o5YALwtttj2iz2TPP73qJx19U8xDIU0edQ0ROAdTLYjVKRntXtsVr4bfTP4qrw6KotUO4PhX1MPEDeQ+xgbanoRJg7sqzlAp7OzMIjzgtwq2wb4s6XRejvTqCXtzUYtvq2pu/ATf1yh7J3+uTwXBRVWizv6qkA8SYjXh5RHLcJ8tY7z0k9z8HIhDngBzqQNkJl1ySXIt9NsKwUksjli++eSR4Cd82rbuGAN7BX5R5w2x2dRjNdtooFdLjqToiczseqSvygeCh8d9wmyG8AtLEbcnbgjalyV5WuMgGWOqf12OEeUx5e4T6A63baCb2+uK9A36rQHZ2ZIbGsQ89Fiu95LUEf3ANzwA90moZG8cVTjgr3RFSNp6r33o7hG47bBHlJFHREmuWg/o6YaLGoNNjfLBRQ59gXsW8G80h3rkXbYnH44QbEd+kCajymzlM2qwOk3nkOVe7swLRh7ijfC3RPW7Kgm+qbM8o4wlKpprbf4AniMfyQGzl7mQ9qCWXuhxC60njq9pQvrQ83gvms+owhiSGIu4Yd2hWkNjKWJAF0u+bp3zSdNU265jnqccKRfrjByBfYHdzlWXmL82SdkGp6Z/cdb0+Ru6KWuq5RDqcMjzIHPOocCB4URYdL9GSlp4vdtKil4spDf1f2yHf1UIuEjh8LeeNEmetsoeGNwc1TYZ9M1h8Z0M4eB18j3qD6dsVDkZdEBkhYqty+HPel4apzXU+SLGOU41PgVvtYEPdB2wf2WBt9wVV5jguFXdG2AneodWNe5EqgxSZih6d9Ocq6wsXrIxLjoch9UU2l7/3qnDTezs8UdU7rqxRuW4fOT4A4V42TKOnopMUbVrXD+14q26tyosBdyjxYXqhNR4ItYMdE0+Uo+Mx4wN4fD0WeEpw9iXOQ+jztSDn0dndOnSW33ofCW66lws2RKTpNBOK5NosVbKsiBKuYKvd54w4VbijkVA+8ZXhUeI4vrvPm5NunefjjKfE2QV7z1M7Z3xz1seDqBTTfaqH15YI9mteq26nCgbCdQtNy1DgD5tHg2gYG3FVFPrW6g7n1fWfNnAV0rpVC00fCmbeRFeONXk6QB0f31oqQAoc8AdFlpeTaK86yMi0WTxuCVgvcecz84fnR8FwxeNO4OjYDZXHAXMNWodV57ZXAtOANQIYts31PHYJYNSI+PTt9rvLO3GS5Jwlv3pS6y7IfEvelyI9Y4wnWRrQojsWiy0+xWmiemuvEU+auHXYa5+gUj6US8NSNaS3DpaZDqtyRxqvMrTTBIYi1IlKm10pJgHguLN31HrCR70y5twX5LZzKWgUT0myY+8pEBOg6n/2JBSOPs14b1jkQj7WPa7eEimBAynlOXQGdCHOP1aLTeUFqf2KRkCfohZdCvKIav4do3VHbvbVyaHDtFa4FwszLvTtzLROOcrFZG7x3f8aTeLNyrkqsoYm76dz6Y0dADbHgsEeS5tvpLBvF+7REmOXuLBdfHYURXKWJ80ogzlXjJbZKUtzwieZ2QZ7rX6/5PaA8KbwwB/xA9wl3sueXPBTLVZ6zHcZvM20U4j41HvHNa/rjtPi11AW6LhBvHrj64YQ1B+b6N8xp9qJVeaIEV80nTO9uOGBv7TkwzgF5KYR7iMqqHPDAPJCe07Hpg3DOg7GcdRvTGBB3lcHxy4P1euqx4LjBVJKTpKdMOyxAB2Fu59nV72i3a5pjkYziE9IGI0OhJ1kyBWq8NA4/2ZzEtb4UeQ3AFyt1R/4mZVaCuS5fB7OdWe/l9HrTAYDb80OKO6fuFuFQ1ZzIHq3i236RuosgVaDQSyGeEk1slRqw7UyI3sSolRaX0QDKT9cpI1gSOjWjt9kH20Q+NSJUnqM9yRBPUeOuttWK0FWNsNIIe7r0p3WU7R2p4mqTb15OcMsLpKkB8SZqvBUi2hRbPfpS5L1EqSpPSutX5kBAnQPxnd8321lmuChn/XRSxCtnQZwZzhN7xhHHdcdYZRC7xqvMSTudmzBgr3gblZI2FpyTWWK+pHI4aRvVdetxE4rcGzVOl5V94XDa9DYEb9zRijh1j5WOTzSPv66oCueuN58az7VjSsKrvq3/Rh5HA13qm0R02GEshOOTEox8WRB3bV5vWoeQSVmOO7RKUuO2Qe6LKoBPSVt4MtBlBKyW6J2YuVAvKNP9vBWHlWL/ruGZ++rIiUIFa6we1y38NigdMA9aFjXtlYQyWe3yzWO3JWEDPoDtjYe1kho1LJZQGYFOzehTDWkZdnAeD8CMrId+ca9QImp8tVVaqPPFClk3j7ZG9HSXZUKaHb2lP2C16PRAYFPlWGIZ4IruChkKvdhSSYy3ZKsAZ4I8EXL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-    "plt.imshow(e1_map)\n",
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-    "The getTangential function uses the e1 and e2 maps as an input, along with a map center, and returns e_tangential and e_cross maps about a given center. \n",
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-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:247: RuntimeWarning: invalid value encountered in divide\n",
-      "  angle = -np.sign(from_cent_2)*np.arccos(from_cent_1/np.sqrt(from_cent_1**2+from_cent_2**2))\n"
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       "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
-    },
+    }
+   ],
+   "source": [
+    "r_bins_mid = 0.5 * (r_bins[1:] + r_bins[:-1])\n",
+    "plt.plot(r_bins_mid,kappa_1D_radial,label='$\\\\kappa(r)$')\n",
+    "plt.plot(r_bins_mid,gammat_1D_radial,label='$\\gamma_t(r)$')\n",
+    "plt.legend()\n",
+    "plt.xlabel('r [Mpc]')\n",
+    "plt.ylabel('Lensing amplitude')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "085bd120-6283-4d8f-adeb-bf4e2c781ba2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "81e0ceb4",
+   "metadata": {},
+   "source": [
+    "## Miscentering\n",
+    "\n",
+    "We now repeat the above procedure, but this time we use an incorrect center (relative to the true hale center) when performing the calculations, the exemplify the impact of miscentering"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 241,
+   "id": "13660944",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:324: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:325: RuntimeWarning: invalid value encountered in divide\n"
+     ]
+    }
+   ],
+   "source": [
+    "# First we define a miscentring parameter\n",
+    "R_mis = 0.05 # Mpc\n",
+    "\n",
+    "# find new center based on R_mis\n",
+    "_phi_Rmis = 2*np.pi*np.random.random()  # isotropic angle for mis-centering\n",
+    "\n",
+    "# mis-centered coordinates\n",
+    "center_1 = R_mis*np.cos(_phi_Rmis)\n",
+    "center_2 = R_mis*np.sin(_phi_Rmis)\n",
+    "\n",
+    "# get tangential and radial profiles\n",
+    "et_map, ex_map, radius_map, angle_map = mod.get_Tangential_and_Cross(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
+    "kappa_radial, gammat_radial = mod.get_Radial(radius_map,angle_map,\n",
+    "                                            r_bins.value,phi_bins,\n",
+    "                                            kappa_map,et_map)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 305,
+   "id": "1cb19534",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_maps_and_profiles(kappa_map,Sigma_map,e1_map,e2_map,et_map,ex_map,\n",
+    "                       kappa_radial,gammat_radial,r_bins):\n",
+    "    '''quickly plot the convergence, e1,e2, ex,et and radial profiles\n",
+    "    '''\n",
+    "    fig, ax1 = plt.subplots(3,2,figsize=(10,18))\n",
+    "    ax = ax1.flatten()\n",
+    "\n",
+    "    plt.sca(ax[0])\n",
+    "    plt.imshow(kappa_map,origin = 'lower')\n",
+    "    plt.xlabel('x ({0})'.format(r_max.unit))\n",
+    "    plt.ylabel('y ({0})'.format(r_max.unit))\n",
+    "    plt.colorbar()\n",
+    "    plt.title(r'$\\kappa$')\n",
+    "\n",
+    "    plt.sca(ax[1])\n",
+    "    plt.imshow(Sigma_map,origin = 'lower')\n",
+    "    plt.xlabel('x ({0})'.format(r_max.unit))\n",
+    "    plt.ylabel('y ({0})'.format(r_max.unit))\n",
+    "    plt.colorbar()\n",
+    "    plt.title(r'$\\Sigma [M_\\odot\\; Mpc^{-2}]$')\n",
+    "\n",
+    "\n",
+    "    plt.sca(ax[2])\n",
+    "    plt.imshow(e1_map)\n",
+    "    plt.xlabel('x ({0})'.format(r_max.unit))\n",
+    "    plt.ylabel('y ({0})'.format(r_max.unit))\n",
+    "    plt.colorbar()\n",
+    "    plt.title('$e_1$')\n",
+    "    \n",
+    "    plt.sca(ax[3])\n",
+    "    plt.imshow(e2_map)\n",
+    "    plt.xlabel('x ({0})'.format(r_max.unit))\n",
+    "    plt.ylabel('y ({0})'.format(r_max.unit))\n",
+    "    plt.colorbar()\n",
+    "    plt.title('$e_2$')\n",
+    "    \n",
+    "    \n",
+    "    plt.sca(ax[4])\n",
+    "    plt.imshow(et_map)\n",
+    "    plt.xlabel('x ({0})'.format(r_max.unit))\n",
+    "    plt.ylabel('y ({0})'.format(r_max.unit))\n",
+    "    plt.colorbar()\n",
+    "    plt.title('$e_t$')\n",
+    "    \n",
+    "    plt.sca(ax[5])\n",
+    "    plt.imshow(ex_map)\n",
+    "    plt.xlabel('x ({0})'.format(r_max.unit))\n",
+    "    plt.ylabel('y ({0})'.format(r_max.unit))\n",
+    "    plt.colorbar()\n",
+    "    plt.title('$e_x$')\n",
+    "\n",
+    "    plt.subplots_adjust(bottom=0.3)\n",
+    "    plt.show()\n",
+    "\n",
+    "\n",
+    "    r_bins_mid = 0.5 * (r_bins[1:] + r_bins[:-1])\n",
+    "\n",
+    "    fig,ax = plt.subplots(1,2,figsize=(10,4))\n",
+    "    \n",
+    "    ax[0].imshow(kappa_radial,origin='lower')\n",
+    "    ax[1].imshow(gammat_radial,origin='lower')\n",
+    "    \n",
+    "    ax[0].set_ylabel('r')\n",
+    "    ax[0].set_xlabel('$\\phi$')\n",
+    "    \n",
+    "    ax[1].set_ylabel('r')\n",
+    "    ax[1].set_xlabel('$\\phi$')\n",
+    "    \n",
+    "    ax[0].set_title(r'$\\kappa$')\n",
+    "    ax[1].set_title(r'$\\gamma_t$')    \n",
+    "    plt.show()\n",
+    "\n",
+    "\n",
+    "    plt.figure()\n",
+    "    r_bins_mid = 0.5 * (r_bins[1:] + r_bins[:-1])\n",
+    "    plt.plot(r_bins_mid,kappa_1D_radial,label='$\\\\kappa(r)$')\n",
+    "    plt.plot(r_bins_mid,gammat_1D_radial,label='$\\gamma_t(r)$')\n",
+    "    plt.legend()\n",
+    "    plt.xlabel('r [Mpc]')\n",
+    "    plt.ylabel('Lensing amplitude')\n",
+    "\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e9720a7d",
+   "metadata": {},
+   "source": [
+    "we can plot all of the results at once using the plot_maps_and_profiles function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 306,
+   "id": "32772d61",
+   "metadata": {},
+   "outputs": [
     {
      "data": {
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\" 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-       "   <g id=\"matplotlib.axis_2\">\n",
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-    "plt.imshow(et_map)\n",
-    "plt.colorbar()\n",
-    "plt.show()\n",
-    "\n",
-    "plt.imshow(ex_map)\n",
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-    "With the radius_map and angle_map, we can calculate the radial convergence profile from the kappa map and the radial tangential shear profile from the e_tangential map, using the getRadial function"
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-   "id": "e3d066a0",
-   "metadata": {},
-   "outputs": [
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-     "name": "stderr",
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-     "text": [
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:298: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n"
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-    "kappa_radial, gammat_radial = mod.getRadial(radius_map,angle_map,\n",
-    "                                            r_bins.value,phi_bins,\n",
-    "                                            kappa_map,et_map)"
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-  {
-   "cell_type": "markdown",
-   "id": "f89da817",
-   "metadata": {},
-   "source": [
-    "plot the radial convergence and tangential shear profiles. Note that these profiles are not averaged over all angles yet, meaning that these profiles are 2D (radial and angular). This is useful for miscentering which leaves anisotropic signatures on the resulting lensing profiles"
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-    "plt.imshow(kappa_radial)\n",
-    "plt.show()\n",
-    "\n",
-    "plt.imshow(gammat_radial)\n",
-    "plt.show()"
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-   "source": [
-    "We can recover the 1D radial convergence and tangential shear profiles as follows"
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-   "execution_count": 14,
-   "id": "5c6174be",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "kappa_1D_radial  = kappa_radial.mean(axis=-1)\n",
-    "gammat_1D_radial = gammat_radial.mean(axis=-1)"
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-   "source": [
-    "Plot the 1D radial profiles"
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-   "execution_count": 15,
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-    "r_bins_mid = 0.5 * (r_bins[1:] + r_bins[:-1])\n",
-    "plt.plot(r_bins_mid,kappa_1D_radial,label='$\\\\kappa(r)$')\n",
-    "plt.plot(r_bins_mid,gammat_1D_radial,label='$\\gamma_t(r)$')\n",
-    "plt.legend()\n",
-    "plt.xlabel('r [Mpc]')\n",
-    "plt.ylabel('Lensing amplitude')\n",
-    "plt.show()"
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-   "source": [
-    "## Miscentering\n",
-    "\n",
-    "We now repeat the above procedure, but this time we use an incorrect center (relative to the true hale center) when performing the calculations, the exemplify the impact of miscentering"
-   ]
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-   "execution_count": 28,
-   "id": "13660944",
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-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n"
-     ]
-    }
-   ],
-   "source": [
-    "# First we define a miscentring parameter\n",
-    "R_mis = 1 # Mpc\n",
-    "\n",
-    "# find new center based on R_mis\n",
-    "_phi_Rmis = 2*np.pi*np.random.random()  # isotropic angle for mis-centering\n",
-    "\n",
-    "# mis-centered coordinates\n",
-    "center_1 = R_mis*np.cos(_phi_Rmis)\n",
-    "center_2 = R_mis*np.sin(_phi_Rmis)\n",
-    "\n",
-    "# get tangential and radial profiles\n",
-    "et_map, ex_map, radius_map, angle_map = mod.getTangential(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
-    "kappa_radial, gammat_radial = mod.getRadial(radius_map,angle_map,\n",
-    "                                            r_bins.value,phi_bins,\n",
-    "                                            kappa_map,et_map)"
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-   "execution_count": 29,
-   "id": "1cb19534",
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-   "source": [
-    "def plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map,ex_map,\n",
-    "                       kappa_radial,gammat_radial,r_bins):\n",
-    "    '''quickly plot the convergence, e1,e2, ex,et and radial profiles\n",
-    "    '''\n",
-    "    fig, ax = plt.subplots(2,3,figsize=[9,6])\n",
-    "    ax.ravel()\n",
-    "\n",
-    "    ax[0,0].imshow(kappa_map,origin = 'lower')\n",
-    "    ax[0,0].set_title(r'$\\kappa$')\n",
-    "\n",
-    "\n",
-    "    ax[0,1].imshow(e1_map,origin = 'lower')\n",
-    "    ax[0,1].set_title(r'$e_1$')\n",
-    "\n",
-    "\n",
-    "    ax[0,2].imshow(e2_map,origin = 'lower')\n",
-    "    ax[0,2].set_title(r'$e_2$')\n",
-    "\n",
-    "\n",
-    "    ax[1,0].imshow(et_map,origin = 'lower')\n",
-    "    ax[1,0].set_title(r'$e_t$')\n",
-    "\n",
-    "\n",
-    "    ax[1,1].imshow(ex_map,origin = 'lower')\n",
-    "    ax[1,1].set_title(r'$e_x$')\n",
-    "\n",
-    "\n",
-    "\n",
-    "    r_bins_mid = 0.5 * (r_bins[1:] + r_bins[:-1])\n",
-    "\n",
-    "    ax[1,2].plot(r_bins_mid, kappa_radial.mean(axis=-1), label=r'$\\kappa(r)$')\n",
-    "    ax[1,2].plot(r_bins_mid, gammat_radial.mean(axis=-1), label=r'$\\gamma_t(r)$')\n",
-    "\n",
-    "    plt.legend()\n",
-    "    plt.show()\n",
-    "\n",
-    "    fig,ax = plt.subplots(1,2)\n",
-    "\n",
-    "    ax[0].imshow(kappa_radial,origin='lower')\n",
-    "    ax[1].imshow(gammat_radial,origin='lower')\n",
-    "\n",
-    "    ax[0].set_ylabel('r')\n",
-    "    ax[0].set_xlabel('$\\phi$')\n",
-    "\n",
-    "    ax[1].set_ylabel('r')\n",
-    "    ax[1].set_xlabel('$\\phi$')\n",
-    "\n",
-    "    ax[0].set_title(r'$\\kappa$')\n",
-    "    ax[1].set_title(r'$\\gamma_t$')\n",
-    "\n",
-    "    plt.show()"
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-  {
-   "cell_type": "markdown",
-   "id": "e9720a7d",
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-    "we can plot all of the results at once using the plot_maps_and_profiles function"
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\" id=\"imagea81b59df13\" transform=\"scale(1 -1) translate(0 -148.32)\" x=\"210.534559\" y=\"-21.704007\" width=\"148.32\" height=\"148.32\"/>\n",
-       "   </g>\n",
-       "   <g id=\"matplotlib.axis_3\">\n",
-       "    <g id=\"xtick_4\">\n",
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c0Q7oLdedn9zBA6M5HKtwQEKlebdGbanPMY6FMTqCR2WBgWjZ1XSjrJIDogQeZL8ZoacoDlb9fBQ4fJ0RkL0PzxsFBnJmvT9TjcoNWKoWNWPZx5/TjXb9+A01QWsDY7RrTxtYo30DFjEooBiFgCUAEMw0CiBTZpyVf8Ndf2iiwDIAY5LtAaKWO8eYratzryjjwBF2Xpe51ll3zG758VbUqRElowECel5hAUzJbAt+zuTNNjeHGRjHANAwRkErCxPNNZUOhnyQhmRqmmEBSs441FRbyhIdmc5aBQBo25nPZSvHLTls0JfMtIps0aUKnGHnTzLwuTw1BsnNtVoewPsacjbigOcAxIMmpOu8nE83vukAIGjjQeXAM1tv1pGVAs1wNGUbChSGdZwqlh1FytrFRApBCZuCJ/7O9RgFSaWcyEzjykt0GQVHo1wf41QHdruxvrZQ92fi+ba5JmWkEtA40ATAlMpM3r+JAAIwA9Da+TxaA8a6JTYxslZRMmeRaKax/o0V+zYxWF4DDDY8RNmLyf7PdTvKTKuV7TT5t/k41af/cq5orvWyTk0VOu4abdTYKJhppahZDhrOdEva8SFpYy1gtDPddGBFC2UtlAZgQh+5QRy7IfoqKvVp8v8toAwBTAE4dOpoYRcCHnq9lLBagzwpyP8eHvQ9bbTKbdXFy2GLPHetL2eXGhs1gNejolI2sk0JNIvJxtpEHjgOQIBxx64ErLWw1kDZKS7JiXM6mdLU0WfBYy0/h5OrlPXDCjxYulbeUQPng6mYmWmvwjYDcmxU7VasU8i/Ypad5oooaLRaVgVw4HGD0wFIK4XZuJmcK7wpZyYHSo0YlqZzOQpI/JqVbzM7psmDAkW2WUgtBc9Gyeso1tnbVg6wvI4BttlDmsBZhyKzwZcP/MojfQg8HawTzTXq4fr6LaouhEi04kGjM9ahYNVWwVgVAeRTHdtoC60d68BMUNryEa/Mj0n/bAooBjjUPPPdEY9pN+4y2PJBXRn4TbYZNdFqZXJdSPul/JwcP4+zh/nWAg+WtDwQwPkz1ud3Va4RWPJvVmlwYKGAyUFkrMLk/5+NhtImljdWYZoMrNUw2npzLb8Af23hVGQZQM12OSbgApaxEJ9zag2YtU/DAzf4XPT/5HcmRfbh/J0jTLSD2QbggCMZ6L2ss6fJloOnmFZgHbTNtVYUjgIkyKTNAhoQIHkFjHJzN85Uc3KanE5ah3kdLE9pZQGrU8DQPwqakEb9IA+C6DIF8NCd9KzAVBMMQnbQ56Bi82SgYdrdbKL1sg0jnH4ixhGFIm9lspXa5Uw2f969PFZnnRwoknmgwDYBSBq2yTo0oBDaMVpDaetNtbSNJAwdAgHz8qcjcOyKbeIPBQei2B8CwJTOS9iGYxaAB0NedynfESaaoExJNqwcaD+50/xIlDrM3wEx2Qi7uC2dgmG21n1ZlLkAhoLHVq43N9Wo+ab9Y93A+Tra2shIAGAmhdkYzB48y0K0MHqQsI6eAT3bBTQhOJD5NrmJ5l6gU3z/xm6mNyjt/giWVZklfz7QEybKwdDwa4ZA023SdYzfTI4NRzeObwaegslmPZXmrBNAJHkxUxGAUNC4Y5OYdMYqGKtxpYwDYDbO/5mvwdcJ/eNVpxG0DDR6zsLQUTEQ0CyWa3hm1J6+3IBP6syBVMqT1XFT0IywTYeIgcN2ds0HER7fEjzUZAvploSTc9YJ684M3NIZY92KgFwoOAJoTnpeMY9jHQNttDPZZtfGPBlcZwM9GSitE3OHBgQ0NdGulvg3C+Mkg1ApQAezNHZJch/ZwUsGPss2DPusggakrrSdOwENxzYd4OKBU6Hzdd7PEDyUgRDMOCQRtpx1AojcawLra059GxNBc1IGWtFImsZJGVytiW0bq3CZNK6TxlUjrTtE1Dzb6CugrwQ8WVAA/rIdYDxKgrqFqJlV3kzjBj1hGNZcK53/kYCmxFRdplqR4qXgoQpmxyvwhHN5udBekhFZJisCT8lkA5aN0sP/lHWUdSsBFJZ5mhA9oyZbAM05MdlmBxSrl+ABFC5G4zJP0Npg1lPUP/g1Dijhz2K62GTyM3aNBqz2W0tp3wd2AYdViH8UHLH7yLk8H2eiiUDTAAx7Lv+N7G43AJPUmeQb92uolIFTYJ1N4OHSyHHYdHwX9tkIHuvLWb9nrSWmW2Adq2yMmAHOh6E6UtCc9RyDAgYKJ6swkajbZZrwrM0SIKD9Yzy7ENCE42QFtAr/WNhs2fbqaU6AQdkmAccG0Lwmy6zqjfkKoOlkG2AwONANnly5m7FPbr8skGmBxxj4NzZ1fAkN2viwsk1Yx1gFo3zImTAPgAiak3I+z+RenMYM7UAFB76r0Xg+T3i+nHDRp4VxCNNMFwtN/lxQwF+jZ5O4b2hgGxQGdQ4M7f7C7+R/CWjyc+5G3gfLeF349EL+htSBU/F1usBTqqtizrHs48+J2WeFTJcWwWPpALCI78T4pBw81irMAODXm2nlwDZ7Z994s81YFQEELObbWc04ewAZq3BRU/R/rkbjeT7hh8lATRbGBy2U8cC5uL/pxUK/WB+SXq7XTgB0/i2e9QCnYAhmXUgrgSZOmuagQ+l4gGV6AFNI2xM0NbYBNoajq+AJGZL0UFCQRtjHVZmZb73sY6k+yzc6OfYJz20NvzuNQjhy79F4vcIqAKVNBI+2FsZqGGtgrIZ7CweYYBxwtAMPAMxW41FfoZXFxWp8ms94PM34qP0qAu/jqKtjmOnFYnq20C/GR9L8ANWhj0iHZEwRALIAxploFCiUdWJaD8vck1kGoOrPDDJNkDZwKqwDLLrtDqDsyZkAiOsPKYBAWClAxfqdaQj7KK0iQKANjFGgizODt0K/Bql8KPqqLLRx0TPKPpR1AngudsLk872YE75/fsJ0mnH1qga2OT1bTJ8MpucZ6uKAAzhAKCzgoQM+giX+75gppvnfIIAqmmj0N7jjsll2NwxTqltaLxEZ4zTAA1TYh2pSAhBQBEySRgDkqm2AiANQdOADgJQnpAxAWEw369lktu4NTifavxrA3yStLK7W4GI1TlZhhnbBAwBnNeNRX6K/86gvAIBnc8L7hzd4f3qDZ+VDzdcAGovTxxn6eYa+muXyTho2TC4p5VlkAYqZHEDMREAzLeeRMc2KZSiIQt/2AuYW7OJ1qcpOoAG69lVrN1xln/xEDwuF9AILuaxMp+UACuYaAUxMywAEq9xGGv6cUW5S1FjrX0BzkTernb9ymrKm5yU4MCmLszK4qAmzdxgmGDzpC85qxlv7jAkWs9X43eMb/OP5HX7QzkybXixOnyxOH2ZMHy7QLzNgLazWUCcXgrBKLWA4OYCYk2cUCpopBU0CngAS329WLemxLzmTrJNdRsCyqjfJ3wBLpU5xG4x07jkgUySfv+PrKoCIs67ydCmIKNg5For+koomWlh3YyOolEv378oopdzKY2tgzAStrXs1AHCTmZOKvy3RKSzBedRXXKxD2VnNeFIXnPUVT5513j+8xT88/AG+myzUrDA9W5w+GJw+XKA/XKDm2dHeCbDQnl1cu+asYE4Ks//fnEDAowjjZAxDAZOZabnTL2aX12SWQp0l6QFMkPG9owGRct0gWhWi6Uwa1yZRjAURrSxeywIaCqI4gHzUzipAaUDZyS/Lce/TaO1WOc/GuLVn0+LfhEgbEBjI4FFf8NY+46yveKef8Q7PeFAzPpgH/N3TN/j1ZKBm4PTR4vz9BdP3n4AXBy6cT7D6BHPSsGcN86BhHhTmhwU85gQCHAUzITHLKGCSgIDKf9sV6yS3TGKG3YJVKvWWZAQwQbZv1hGkE0SxCq5cCUglf6bmC0afxuVjJ1cDMCiIoJaBEgeRZx+/sYbbZGOC0f71Am0xa43ZaFxng8uk3YqAacLVaFyNxsUuvs4Eiyd9wTs84yv9CV/pT3h5nPCrNz/D/z7/MfQVePx+xun9J6jff3BqP55hpwn2cYJ5mnB9mjA/aQ8aYD4r2Agalfg2ETjhmhh2ScAyyip3xijidjtkv9XRJROrISIwla62FBzI2YUJb1PAJV+Oo6ZbzqwePJawkfJvbhr/W2mL+aqhJ4Pr5JbRPGvjJjfnEz7NZ7yYE57NKfo7D2rGO/WCb6dP+Pfn3+Af3n2D//X4S0yfgIfvXqB/+z3sywXq7RPwcIb5yQOub8+4vp1wfeOYZn5wgJnPivgzC2ho1GwNmjVQ9gLJZoBwbXTIXkDJ5bhXp2t90riYVn8ubkqlomTeJtMnYylVfA/FhgzZOc88yjnmy2/XptEWSrsFm9ovo3m+uMnNx9OM75+f8P7hDX73+AbvH97ig3nAy+OEJ/Ub/Gy64D+/+RX+x7v/hOff/xTn//tb2B9+gHr3Duard7h+/YTLT8+4vtW4PilcHx3TGA8YcwKgXUAg8WFKjFIBSREgUnDcABjV9g+U19k7WtifUSouUL0dRf8rt19YLZt8NWA1cFQKrAxw1q9ydgs2LS76BDVZfNQW02nG+5OLnv3Dwx/g756+wa/e/Ay/fvuv8F/e/g1+efqA//jN/8Nf/+ZnsN+9h/r2a1x+8Q2ev33Ey1fascwjIsuYE+/0I+pBuoP6KcVrW3Vhu7+yvtsirwGEXlH/9s//rHcY//hkD6cyH0zMU9x6ZorBBw1AW6iTgT4bPDxc8c1PPuBPv/4Nns0J/+fP/gPUbPHhDydcvnJgMSe4kLO2azZh2l3pWnhIbL7+f2Fy6n76/wiFLssX5Wf9Ks2ft8v/KhxbkLc6VVzIOX0Cnn//Ff7mNz+DOSn8u//2l3jUM/7ytz/Hxx/e4Pn5DHPRsLMGZuU/iaCWOmmAg9MBYEd990r7L2Pmzj/z4WXzKxSt8pLBxAxERY/9XGn6Wy2vNZPdaPQVUFfEtWenjxaP3894+O7F+TTfvccP//VP8ahn/Pd//T/xqz98i7/4+Ev89Yc/xq8/fI33n97gh5czni9nXK8a83WCMQrWKNjZOy0ZqJZJ4CWgEpcxlUBW6rsG5Rx+v+5AXgU4N+vYwg2WgALIgEH+ZwFCmIT+r2f492kCYCymF7oiwOD8/QWn959c9OyHH6C+/Ro//HzCX/725/jVH77Fvzl9wLu3f4VfnH+Lv336I/z9p2/xTy/v8P75DT5cHvDxcsbLdcJ11rheJ1ijYIyGNYA1DkjufywgsnDLhWgfra6zEErLlxnlh5LgDZHV/eg1BV8BaIcBZxM4NgKDbb9yrLj0HCQ+rQUUFcywbH+A5dUAu6w9+zDj9MFNbqrff3Ah53fvcPnFN7j8ROHjD2/wFx9/iXdv/wpv9RV/cvoOD2rGW/2Cr88/xT+ef4LfXd7g+5cnfLye8el6wst1wmWeMM8a86xhZjdvFICzBpJNmYn0qw2rK/L+ygGVh/7pTajdy1LwJpPmWKqVPwhUuwFnGCiScj0A4ersAUmWngOFmmQ5WGCQbaxhF7PsYuP7NNMng9OnGdMPbhlNWBGg3j7BfPUOz98+Yn4Cnp/P+OsPf4xfnH+LPzl9B60MvtIf8fPzewDwKxCueNBX/PPlER+mB3yaznieJ89Ak9s9Z9bRlAsgUhREOXjoH53XCt0S3ytfOpSbH2OPad+XBk12v7nbLx5vrYjqoGx+H6dL9jaxSvUKgRLrZFmGB0sEDIiDT74aoOkWTmSPAPo+zfQ8Q3+aoV9mt/YMgH08Aw9nXL9+wstX2i2ZuWj8+sPX+NunP8KDmvGV/ggAeFIXfDV9xOyvTvtFpCft/s7zCc/6hJfZ4DJrXLUDkDEq/lmjXVTOWsCoyDx2BR61mGax37J5LQskK9VVxkrc/eJOx/Il26+aJBuPJXbslOFXp8VyY0YB+lklpgewhHSGXQACFGqWRaaxxEQjewRc/JubLwbqYtyrAda6BZsPZ1itYX7y4CY337j5GTtrvP/0Bn//6Vu81S/4+fk9HtSM2eq4QPStfsE86WQt3LKvm8WkNS7aOv/HaJjAQMo4rBi9YCOCKBxnoAmsREFC2YiwC12tnn9FeyUEcKu05KaRNrlq6LRbD4gGANS9y41INoBlhFUAIbNk5xS5+St2Afx3Z5YycSum1RcDFpYJZlrY9yxsrKEv/nVnY8lLaH6Vs9awj5NfRqMxP8J9fGpW+OHljH96eYevzz8FAHw1fcRZzckKa/d+zxVm0skr20pZqPkEBcR93K4+3fgAglHGRePCam5lF7/HLLiJIAoAiiCxy3l6I0ogysy+oo9UM7EEK4e7QDQAoK4NCZvSynMLZiG/W+yy/EYGpIxhyHH+Uad8A3R208AryRded1bw79NomJN2CzbfTrg++XVn2gIGeL6c8f75Df7x/BNMymCGwpNyPtHs3z6dlHst+6JnPNgrZuteMwCQvNoAuE+VXGeNWSn/5Tn3rpExbvMRY9UCEhUYyAEqYaEw4EsstLpBoWsHQETrysdEB4hEABKCR7zpelNqeXrYpZG2qknILjGdAUx+rPL/KWgo49CPOjHb0i67bFrQ+ROrlXtz0/+2Z43rk1uweX30Zpp2ul6vGv/88ojfXd7gUV8BAG/1S/LqdZAJJr40d1UGJzVHAOWijIKrze+boPzmJNb6T8mHvrLR74m7MlDA0OP8plQAFP2ieM/UGhwtJiqBqAKgvcAj+rBUVY4CTCe7JPVygPH68OHl7DfWLEPZZmEc5lMb8UNPNqkjXETcI2BaXnM2Dzp5NcCcEG/gfJ3wfD3h+5cnPPiNPebJ+TiTj1JQ8CQbImrjNg3RCieojH3c5iMzPOv4PRWMUYB2n1w0AJReGMbGPlo21UpNtoJ9ldhNWAsBEctCtFwPC1WCCtVxLQDPfu/jJOkHMcxWwIRzmVm2Ag3xbVYmWsxPWCWetyu2WpR0q5cBLLvSTP7NzYfl1QBzJts1WcAYhZfrhI/XM/758oiz39jjUV8j6wAOPDPZOMRtw6vj/5NyADJWYfIftzJ+N1GLsJeC23zEfWJx2QgUiLu1wXrFwhcfwsaNscPpcX6zOADZ9HcCoJCvBZZBAG2Za6wCp1rxEaCRmGTkd2lNWDyXm2X+fI1lSiYaSFr+zc1k/2YWNF4VrcgSfgcQc1aRaWx8Y9OPJz/ncp01Pl1P+DA94BQG/aRx0XOywWFpPzf6N2kDM7u3VydtARjA6Mg8YfNFt58cuQ/RPFvYJzHfSjQRTlnfwfn4UGn2BWMMA+VgWQGFSUOhXTTA02Cdba9Oc5rk7XcCBjiOZeL5AdDkjLOqI2/fX4Rb++mHV3gaKzgz7eQ21TBnt0+A2ysACePYWeF6dROan6YzTv7LbwYKD/aKSS3f23F7UE8xNL3aVZQAyT1X3D4KVlm3jW8EDQMeG77swLPP4vTXvH1yowTsA69jwj7kXDf77Mg8ReCIw8JUA0kdR7OM12UX0JD05bdNjlkwkwtyZlk6gOi+ZmFjjcA20MjGnmOdyzzheZ5wnk9xs/bZqmxDd8QN3U3yzUIXjp7Jb2NV/AR9fE/Phs+g0P8RIdIET2AVyjTwA5Z2wxb2yfNxx8W0TvBUWGdslxuu5bzNBqscxTKrfLZwXABNKz1nm+XPLiqEP7/FU9xm1l+oVQ48blONdGMNQ15Gg4WzpPyk5ct1wrM+LQwzKVzjJ0XST4lc/d4G1HwLGyYahnVmi5jm8tL/F4i0wOO6iAFPuPhEbsA+QvD0CgucLur6jEGT1M0BZQUiwjb5JflXqMMDF8qbLwEwYSypBUjhVeewsYadQllLK4Y1wDxrXOcJL7NJviN6UrM333T8eBUAso+1jsf5nE68/ox1LAJgrH+tPININtApeNKwVcHH2cg+KgdaDSxC8PSyTt+GhKu0+wZNUhcz4HMQqSwfyzaMxE73TGMBH5JSSZnARnSHzdWmgWFjDfIEtUbBzG73nMusMWkNNZ/iPm7GmuJnE/PtqUx2z5QfRFphxTrLN1Dd6AmAUcDCOnapp2m2fa7gYWTX1wruDTScH9I0xbg6KpKAJhsT6c1GyjjJDptks0C/jRPVI6xqnv2CzYu2Sd8ZrXzoOQ0UAEhBE0yphqkSx7JnnQiYir+TmkyfCXg2yLavTnflTw9vBhqsjzkw5Gyz1qXS6xE0Pr6klroS9iBmmolMo6JfE/0jKr4C61c1uz3bdMIuJyhMhHHoZ+IDaOL3TCv3jX73NP+dsw7tuMTfIabaq4OnJRv8Hfmm6wIdpGW2gKbYLlfWp7OsUWIbro6C5OziTBg6QMg3NyPbYNmRxv+BbBYY8uW6RuYx7iNUYW9qwIHCsY5jHDcnQz/+u4AmfHO0BqDYB2oNlBXrcGWiverz54O+NMD3AE+pDHfMiNRcWwFHZOPlndlhog2BhmuL6sDlr5loLZF0bpYvfgHNDwzlGShlGw8e5qsB6101A13ZBTRWxVXNV7gFm0HCigD6leuQHv7PQVALGARJBn4xU9lkS4IFyZOmkIbsXJKW1c+Bp9dkk7AOo9/xew502pUldkjO5SYal6dRHxdJ4yJusYjfbD2tfHmARhVUei+obxPBQ0GTm2nKpk8Xi7W5Nmso5d6xCRJWBIQJTkMuPDfTDMMUNF8uSuWjNQtPM/lpXRF8tGNaJtsW2dmf4UT2YankuJNtaN5SvgpYRH5NrkuBbTZLbqZn1cdjSoYRENRUYz61QRhpJZ5xlAWsf4fGGOVeDfCLM4FgJjlgaOaJEf0dpGab+39Lx/jrDxYawzpVk+0If6dUhj1O25GYa8cyzo4mmrQdKiL2GZD8HtOI2lqJjG1UFkFT6W/iHnidw54ADjzudWc3KaoU/KsB7rOJk9/HOgCIExoskJhqYskGH+cfcfl663Vp6DfZdpZ9gbNB0SETrcZUJenRcWWKeUueM9fzZqhvE4FT+BJalm+tc/B1HIgC67jJSbdA0zGMcSalsssylaxjqdm2/EZ8AzSYcT2Aao7R2uA/0mTrUrJPjtuso5Ntqmm9ujTaqOodfBMun+LBA/AP0cW/UZFZ4C2rHDzW+zfUtFOWmDeBeYwLOFjj3twEAKW8n2G0ZxxEAJWe7hxouDzW1kHEMkuBEUSBBraRA1hnI5A616pVnkJHs02pvR2fIiXbNomiUfDUmg+ACb8zPyb/1iYbhk6UQGSeMJiNUf7NTQWt3fetwytts3UDVRfqDD6NTZiHDxqEfBKRRuGK0TTgdVin04SsA2dUaUm5XrbhImmV8t3+DNOpFDAceEI5Gm2LYAl1qgUouT9D/Zrkj7uu+BfA4/cIMEB4m1MpFd/eXFZQe1WYKBv9TUFTZiBGt4okbFQbmLm5xuZpsE5RCUEeRloBgmFTTTowi2ZaTXpvUGf+vFNWnbQ4NctxZpql9TGp1LeJPk4GGhAGUmnZpfL0t7VwG2go92qAtja+9hzeownBAQqgEmPQSFuejzPTWsct6TbXpAO/ZK7tUTcjr77pem3QNwGxB41nnZeASBFfh4AnFCuqRZiDggYUQCumsQ3GURnz+GCB0YA2MdKmtYmVhKwtCzD+JhE3OrjXYKlUKJWWabS3mbazJMAZDtf2luvOn5lpR3Uo53CqNCmqVKsDKTA48IQ8lJWaD0mPhGSbJoVosrk3NnV8TSAQoQVW0bVYJWO2xT0IM/Y5RHJ/pjtcjb7xMArIrFzHawXCi6F+RiG9Ve5Q4cABwjQMy6zYpvAYT5x9/38OmoRt8mU24LvBvSNjUz/HIA4y46sK4KG2pns1AOQVAUZvBiAc+yTMQ8skdbFN7CMdLDU0p9MB2lc31VZyIwDlJln0YRggiVTMfJTcv0lYZWWu2aSO5N5RllWITBN9HVgoreJpYxDZRoWQdIgAehCtrqdgltXYKD9/qNyh2Xb83tE3qEcqbKSEYZXlee2ztBwF7kHMgUaTPHkZyRgM5hk5jns++wrcZaR0SdnG2rXZVnL41+yTX2Sm2+cog6C8P8bZSarhxJxhOPAwJhrAg4iLiHE+TjyfMxLSc+uLIfrFY7/QMvg98boUAx6iWEFKAYASaGI6Wxlf549JtgPn6MDAVsmeKK34PAu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\" id=\"image1b641d4b55\" transform=\"scale(1 -1) translate(0 -148.32)\" x=\"33.2875\" y=\"-203.144007\" width=\"148.32\" height=\"148.32\"/>\n",
-       "   </g>\n",
-       "   <g id=\"matplotlib.axis_7\">\n",
-       "    <g id=\"xtick_10\">\n",
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     }
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    "source": [
-    "plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map,ex_map,\n",
-    "                       kappa_radial,gammat_radial,r_bins)"
+    "plot_maps_and_profiles(kappa_map,Sigma_map,e1_map,e2_map,et_map,ex_map,\n",
+    "                       kappa_radial,gammat_radial,r_bins) "
    ]
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   },
   {
    "cell_type": "code",
-   "execution_count": 31,
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    "id": "38b199f1",
    "metadata": {},
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    "source": [
     "# define miscentring distribution\n",
-    "R_mis_max = 1 \n",
+    "R_mis_max = 0.5\n",
     "N_R_mis   = 15\n",
     "R_mis_arr = np.insert(np.logspace(-2, np.log10(R_mis_max), N_R_mis-1), 0, 0)"
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    "id": "c17883c2",
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     "scrolled": true
@@ -11009,68 +12070,38 @@
      "name": "stderr",
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-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:248: RuntimeWarning: invalid value encountered in divide\n",
-      "  angle = -np.sign(from_cent_2)*np.arccos(from_cent_1/np.sqrt(from_cent_1**2+from_cent_2**2))\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n"
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:273: RuntimeWarning: invalid value encountered in divide\n",
+      "  tangential shear map\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:324: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:325: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:324: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:325: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:324: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:325: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:324: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:325: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:324: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:325: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:324: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:325: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:324: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:325: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:324: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:325: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:324: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:325: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:324: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:325: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:324: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:325: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:324: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:325: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:324: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:325: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:324: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:325: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:324: RuntimeWarning: invalid value encountered in divide\n",
+      "/Users/alessandrafumagalli/DESC/CLMM/clmm/model_profile.py:325: RuntimeWarning: invalid value encountered in divide\n"
      ]
     }
    ],
@@ -11091,16 +12122,16 @@
     "    center_1 = R_mis_arr[j]*np.cos(_phi_Rmis)\n",
     "    center_2 = R_mis_arr[j]*np.sin(_phi_Rmis)\n",
     "\n",
-    "    et_map[j], ex_map[j], radius_map[j], angle_map[j] = mod.getTangential(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
+    "    et_map[j], ex_map[j], radius_map[j], angle_map[j] = mod.get_Tangential_and_Cross(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
     "\n",
-    "    kappa_radial[j], gammat_radial[j] = mod.getRadial(radius_map[j],angle_map[j],\n",
+    "    kappa_radial[j], gammat_radial[j] = mod.get_Radial(radius_map[j],angle_map[j],\n",
     "                                                      r_bins.value,phi_bins,\n",
     "                                                      kappa_map,et_map[j])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 246,
    "id": "22ba0469",
    "metadata": {},
    "outputs": [
@@ -11115,7 +12146,7 @@
        "  <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n",
        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2025-02-06T12:33:35.708320</dc:date>\n",
+       "    <dc:date>2025-06-10T13:41:25.339216</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
        "    <dc:creator>\n",
        "     <cc:Agent>\n",
@@ -11146,20 +12177,20 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#pa99d65b8bc)\">\n",
+       "   <g clip-path=\"url(#p74325373a9)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
-       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+       "       <use xlink:href=\"#mc40aaccc2b\" x=\"33.431744\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_1\">\n",
@@ -11195,7 +12226,7 @@
        "    <g id=\"xtick_2\">\n",
        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"91.129354\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc40aaccc2b\" x=\"91.129354\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_2\">\n",
@@ -11236,7 +12267,7 @@
        "    <g id=\"xtick_3\">\n",
        "     <g id=\"line2d_3\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"148.826965\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc40aaccc2b\" x=\"148.826965\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_3\">\n",
@@ -11274,12 +12305,12 @@
        "    <g id=\"ytick_1\">\n",
        "     <g id=\"line2d_4\">\n",
        "      <defs>\n",
-       "       <path id=\"mc74ca6bf58\" d=\"M 0 0 \n",
+       "       <path id=\"m6e7ec76174\" d=\"M 0 0 \n",
        "L -3.5 0 \n",
        "\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </defs>\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"33.2875\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_4\">\n",
@@ -11292,7 +12323,7 @@
        "    <g id=\"ytick_2\">\n",
        "     <g id=\"line2d_5\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"33.2875\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_5\">\n",
@@ -11323,7 +12354,7 @@
        "    <g id=\"ytick_3\">\n",
        "     <g id=\"line2d_6\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"33.2875\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_6\">\n",
@@ -11338,7 +12369,7 @@
        "    <g id=\"ytick_4\">\n",
        "     <g id=\"line2d_7\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"33.2875\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_7\">\n",
@@ -11387,7 +12418,7 @@
        "    <g id=\"ytick_5\">\n",
        "     <g id=\"line2d_8\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"33.2875\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_8\">\n",
@@ -11402,7 +12433,7 @@
        "    <g id=\"ytick_6\">\n",
        "     <g id=\"line2d_9\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"33.2875\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_9\">\n",
@@ -11495,15 +12526,15 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#pdd8f556f29)\">\n",
+       "   <g clip-path=\"url(#p0db0713516)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
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\" id=\"image5f64d4d286\" transform=\"scale(1 -1) translate(0 -148.32)\" x=\"210.534559\" y=\"-21.704007\" width=\"148.32\" height=\"148.32\"/>\n",
+       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\" id=\"image1f6603d4c3\" transform=\"scale(1 -1) translate(0 -148.32)\" x=\"210.534559\" y=\"-21.704007\" width=\"148.32\" height=\"148.32\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_3\">\n",
        "    <g id=\"xtick_4\">\n",
        "     <g id=\"line2d_10\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"210.678803\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc40aaccc2b\" x=\"210.678803\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_11\">\n",
@@ -11516,7 +12547,7 @@
        "    <g id=\"xtick_5\">\n",
        "     <g id=\"line2d_11\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"268.376413\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc40aaccc2b\" x=\"268.376413\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_12\">\n",
@@ -11531,7 +12562,7 @@
        "    <g id=\"xtick_6\">\n",
        "     <g id=\"line2d_12\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"326.074023\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc40aaccc2b\" x=\"326.074023\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_13\">\n",
@@ -11548,7 +12579,7 @@
        "    <g id=\"ytick_7\">\n",
        "     <g id=\"line2d_13\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"210.534559\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_14\">\n",
@@ -11561,7 +12592,7 @@
        "    <g id=\"ytick_8\">\n",
        "     <g id=\"line2d_14\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"210.534559\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_15\">\n",
@@ -11576,7 +12607,7 @@
        "    <g id=\"ytick_9\">\n",
        "     <g id=\"line2d_15\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"210.534559\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_16\">\n",
@@ -11591,7 +12622,7 @@
        "    <g id=\"ytick_10\">\n",
        "     <g id=\"line2d_16\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"210.534559\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_17\">\n",
@@ -11606,7 +12637,7 @@
        "    <g id=\"ytick_11\">\n",
        "     <g id=\"line2d_17\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"210.534559\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_18\">\n",
@@ -11621,7 +12652,7 @@
        "    <g id=\"ytick_12\">\n",
        "     <g id=\"line2d_18\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"210.534559\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_19\">\n",
@@ -11705,15 +12736,15 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p142c2415fd)\">\n",
+       "   <g clip-path=\"url(#pc3a829fe3b)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
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\" 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+       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id=\"image42183a63c3\" transform=\"scale(1 -1) translate(0 -148.32)\" x=\"387.781618\" y=\"-21.704007\" width=\"148.32\" height=\"148.32\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_5\">\n",
        "    <g id=\"xtick_7\">\n",
        "     <g id=\"line2d_19\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"387.925862\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc40aaccc2b\" x=\"387.925862\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_21\">\n",
@@ -11726,7 +12757,7 @@
        "    <g id=\"xtick_8\">\n",
        "     <g id=\"line2d_20\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"445.623472\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc40aaccc2b\" x=\"445.623472\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_22\">\n",
@@ -11741,7 +12772,7 @@
        "    <g id=\"xtick_9\">\n",
        "     <g id=\"line2d_21\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"503.321082\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc40aaccc2b\" x=\"503.321082\" y=\"170.024007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_23\">\n",
@@ -11758,7 +12789,7 @@
        "    <g id=\"ytick_13\">\n",
        "     <g id=\"line2d_22\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"387.781618\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"387.781618\" y=\"169.879763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_24\">\n",
@@ -11771,7 +12802,7 @@
        "    <g id=\"ytick_14\">\n",
        "     <g id=\"line2d_23\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"387.781618\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"387.781618\" y=\"141.030958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_25\">\n",
@@ -11786,7 +12817,7 @@
        "    <g id=\"ytick_15\">\n",
        "     <g id=\"line2d_24\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"387.781618\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"387.781618\" y=\"112.182153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_26\">\n",
@@ -11801,7 +12832,7 @@
        "    <g id=\"ytick_16\">\n",
        "     <g id=\"line2d_25\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"387.781618\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"387.781618\" y=\"83.333348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_27\">\n",
@@ -11816,7 +12847,7 @@
        "    <g id=\"ytick_17\">\n",
        "     <g id=\"line2d_26\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"387.781618\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"387.781618\" y=\"54.484543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_28\">\n",
@@ -11831,7 +12862,7 @@
        "    <g id=\"ytick_18\">\n",
        "     <g id=\"line2d_27\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"387.781618\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"387.781618\" y=\"25.635738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_29\">\n",
@@ -11881,15 +12912,15 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p5e41af0ce7)\">\n",
+       "   <g clip-path=\"url(#pe3ef1f2d5e)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
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\" 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+       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id=\"image753545e292\" transform=\"scale(1 -1) translate(0 -148.32)\" x=\"33.2875\" y=\"-203.144007\" width=\"148.32\" height=\"148.32\"/>\n",
        "   </g>\n",
        "   <g id=\"matplotlib.axis_7\">\n",
        "    <g id=\"xtick_10\">\n",
        "     <g id=\"line2d_28\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"33.431744\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc40aaccc2b\" x=\"33.431744\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_31\">\n",
@@ -11902,7 +12933,7 @@
        "    <g id=\"xtick_11\">\n",
        "     <g id=\"line2d_29\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"91.129354\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc40aaccc2b\" x=\"91.129354\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_32\">\n",
@@ -11917,7 +12948,7 @@
        "    <g id=\"xtick_12\">\n",
        "     <g id=\"line2d_30\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"148.826965\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc40aaccc2b\" x=\"148.826965\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_33\">\n",
@@ -11934,7 +12965,7 @@
        "    <g id=\"ytick_19\">\n",
        "     <g id=\"line2d_31\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"351.319763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"33.2875\" y=\"351.319763\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_34\">\n",
@@ -11947,7 +12978,7 @@
        "    <g id=\"ytick_20\">\n",
        "     <g id=\"line2d_32\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"322.470958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"33.2875\" y=\"322.470958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_35\">\n",
@@ -11962,7 +12993,7 @@
        "    <g id=\"ytick_21\">\n",
        "     <g id=\"line2d_33\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"293.622153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"33.2875\" y=\"293.622153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_36\">\n",
@@ -11977,7 +13008,7 @@
        "    <g id=\"ytick_22\">\n",
        "     <g id=\"line2d_34\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"264.773348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"33.2875\" y=\"264.773348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_37\">\n",
@@ -11992,7 +13023,7 @@
        "    <g id=\"ytick_23\">\n",
        "     <g id=\"line2d_35\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"235.924543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"33.2875\" y=\"235.924543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_38\">\n",
@@ -12007,7 +13038,7 @@
        "    <g id=\"ytick_24\">\n",
        "     <g id=\"line2d_36\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"33.2875\" y=\"207.075738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"33.2875\" y=\"207.075738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_39\">\n",
@@ -12084,15 +13115,15 @@
        "z\n",
        "\" style=\"fill: #ffffff\"/>\n",
        "   </g>\n",
-       "   <g clip-path=\"url(#p56b7f0f743)\">\n",
+       "   <g clip-path=\"url(#p29a40bb2b2)\">\n",
        "    <image xlink:href=\"data:image/png;base64,\n",
-       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\" 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        "   </g>\n",
        "   <g id=\"matplotlib.axis_9\">\n",
        "    <g id=\"xtick_13\">\n",
        "     <g id=\"line2d_37\">\n",
        "      <g>\n",
-       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"210.678803\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc40aaccc2b\" x=\"210.678803\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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        "     <g id=\"text_41\">\n",
@@ -12105,7 +13136,7 @@
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-       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"268.376413\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc40aaccc2b\" x=\"268.376413\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_42\">\n",
@@ -12120,7 +13151,7 @@
        "    <g id=\"xtick_15\">\n",
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        "      <g>\n",
-       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"326.074023\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc40aaccc2b\" x=\"326.074023\" y=\"351.464007\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
        "      </g>\n",
        "     </g>\n",
        "     <g id=\"text_43\">\n",
@@ -12137,7 +13168,7 @@
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+       "       <use xlink:href=\"#m6e7ec76174\" x=\"210.534559\" y=\"322.470958\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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        "      <g>\n",
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+       "       <use xlink:href=\"#m6e7ec76174\" x=\"210.534559\" y=\"293.622153\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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@@ -12180,7 +13211,7 @@
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-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"264.773348\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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@@ -12195,7 +13226,7 @@
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-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"235.924543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"210.534559\" y=\"235.924543\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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@@ -12210,7 +13241,7 @@
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        "      <g>\n",
-       "       <use xlink:href=\"#mc74ca6bf58\" x=\"210.534559\" y=\"207.075738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#m6e7ec76174\" x=\"210.534559\" y=\"207.075738\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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@@ -12281,12 +13312,12 @@
        "    <g id=\"xtick_16\">\n",
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        "      <g>\n",
-       "       <use xlink:href=\"#ma7a60c1ff8\" x=\"391.479085\" y=\"353.211066\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
+       "       <use xlink:href=\"#mc40aaccc2b\" x=\"391.597813\" y=\"353.211066\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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        "   <g id=\"matplotlib.axis_1\">\n",
        "    <g id=\"xtick_1\">\n",
        "     <g id=\"line2d_1\">\n",
        "      <defs>\n",
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        "      <g>\n",
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        "     <g id=\"text_1\">\n",
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        "     <g id=\"line2d_2\">\n",
        "      <g>\n",
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-       "       <use xlink:href=\"#m290e0039d4\" x=\"40.603125\" y=\"84.002489\" style=\"stroke: #000000; stroke-width: 0.8\"/>\n",
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        "   </g>\n",
-       "   <g clip-path=\"url(#p7753a0a83d)\">\n",
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   {
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+   "execution_count": 247,
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@@ -14061,13 +15943,16 @@
    ],
    "source": [
     "for i in range(N_R_mis):\n",
-    "    plt.plot(r_bins_mid,kappa_radial[i].mean(axis=-1))\n",
+    "    plt.plot(r_bins_mid,kappa_radial[i].mean(axis=-1),label='misc=%1.2f' %R_mis_arr[i])\n",
+    "plt.xlabel('r [Mpc]')\n",
+    "plt.ylabel('Convergence radial profile')\n",
+    "plt.legend(ncol=3)\n",
     "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 248,
    "id": "2864956a",
    "metadata": {},
    "outputs": [
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        "   <cc:Work>\n",
        "    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
-       "    <dc:date>2025-02-06T12:33:36.006858</dc:date>\n",
+       "    <dc:date>2025-06-10T13:41:25.699260</dc:date>\n",
        "    <dc:format>image/svg+xml</dc:format>\n",
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    ],
    "source": [
     "for i in range(N_R_mis):\n",
-    "    plt.plot(r_bins_mid,gammat_radial[i].mean(axis=-1))\n",
+    "    plt.plot(r_bins_mid,gammat_radial[i].mean(axis=-1),label='misc=%1.2f' %R_mis_arr[i])\n",
+    "plt.xlabel('r [Mpc]')\n",
+    "plt.ylabel('Gamma_t radial profile')\n",
+    "plt.legend(ncol=3)\n",
     "plt.show()"
    ]
   },
@@ -14690,6 +17535,22 @@
    "metadata": {},
    "outputs": [],
    "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "032de18c-3014-4bdb-a99f-713a22857d33",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3ae1b92d-bc33-4c4d-99b4-8266f38c4709",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
diff --git a/examples/demo_modelling.ipynb b/examples/demo_modelling.ipynb
deleted file mode 100644
index d7bdc6e2c..000000000
--- a/examples/demo_modelling.ipynb
+++ /dev/null
@@ -1,12123 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 36,
-   "id": "45308159",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%matplotlib inline\n",
-    "%config InlineBackend.figure_format = 'svg'\n",
-    "\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "import sys\n",
-    "from astropy import units as un\n",
-    "import pyccl as ccl\n",
-    "import clmm\n",
-    "from clmm import Cosmology\n",
-    "from clmm.support import mock_data as mock\n",
-    "from clmm.galaxycluster import GalaxyCluster\n",
-    "from clmm.constants import Constants as const\n",
-    "\n",
-    "# profile modelling package\n",
-    "import clmm.model_profile as mod"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "7ba07a0d",
-   "metadata": {},
-   "source": [
-    "Make sure we know which version we're using"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "bbd94d3a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'1.15.0'"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "clmm.__version__"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "66c330d7",
-   "metadata": {},
-   "source": [
-    "The modelling module can be used to create 2D lensing maps. This allows us to forward model systematics, starting at the map level. In this notebook, we use miscentering as an example systematic."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "909edd57",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# specify parameters for NFW halo\n",
-    "c    = 10   #concentration\n",
-    "z_l  = 0.5  #lens redshift\n",
-    "z_s  = 1.0  #source redshift\n",
-    "Mass = 1e14 * un.M_sun\n",
-    "\n",
-    "# define physical size of grid\n",
-    "r_min = 0 * un.Mpc\n",
-    "r_max = 50 * un.Mpc\n",
-    "\n",
-    "# number of pixels in grid\n",
-    "npix = 512\n",
-    "\n",
-    "# define physcial size of a pixel\n",
-    "dx = r_max/npix\n",
-    "\n",
-    "# define the center of the map (in Mpc)\n",
-    "center_1 = 0\n",
-    "center_2 = 0\n",
-    "\n",
-    "# define radial and angular bins\n",
-    "N_r_bins   = 30\n",
-    "N_phi_bins = 25\n",
-    "r_bins   = np.insert(np.logspace(-2, np.log10(r_max.value), N_r_bins), 0, r_min.value) * un.Mpc\n",
-    "phi_bins = np.linspace(-np.pi, np.pi+0.01, num=N_phi_bins+1)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "de3d76d6",
-   "metadata": {},
-   "source": [
-    "Now we can create the convergence maps"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "5b51bbc8",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "WARNING: function 'sqrt' is not known to astropy's Quantity. Will run it anyway, hoping it will treat ndarray subclasses correctly. Please raise an issue at https://github.com/astropy/astropy/issues. [astropy.units.quantity]\n"
-     ]
-    }
-   ],
-   "source": [
-    "# set cosmology\n",
-    "cosmo = ccl.Cosmology(Omega_c=0.25, Omega_b = 0.05, h=0.7, sigma8=0.8, n_s=0.96)\n",
-    "\n",
-    "# lensing_map has the option to return either Sigma map or the convergence map\n",
-    "lensing_map = mod.profiles(cosmo, Mass, c, z_l, z_s, compute_sigma=False) \n",
-    "\n",
-    "# make map\n",
-    "kappa_map = lensing_map.kappa_NFW_2D(npix,r_max) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "b0dc4b6c",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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-    "axlim = 2*r_max.value\n",
-    "plt.imshow(kappa_map.value,extent=[-axlim,axlim,-axlim,axlim],origin='lower')\n",
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-    "Repeat the procedure for a Sigma map"
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-    "# lensing_map has the option to return either Sigma map or the convergence map.\n",
-    "lensing_map = mod.profiles(cosmo, Mass, c, z_l, z_s, compute_sigma=True) \n",
-    "\n",
-    "# make map\n",
-    "Sigma_map = lensing_map.kappa_NFW_2D(npix,r_max)"
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-    "axlim = 2*r_max.value\n",
-    "plt.imshow(Sigma_map.value,extent=[-axlim,axlim,-axlim,axlim],origin='lower')\n",
-    "plt.xlabel('x ({0})'.format(r_max.unit))\n",
-    "plt.ylabel('y ({0})'.format(r_max.unit))\n",
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-    "We can transform from the convergence to the shear with the Kaiser Squires algorithm, returning the e1 and e2 shear maps."
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-   "execution_count": 8,
-   "id": "eec34ea3",
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-   "outputs": [
-    {
-     "name": "stderr",
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-     "text": [
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:202: RuntimeWarning: divide by zero encountered in divide\n",
-      "  oper_1  = - 1./(k[:, None]**2 + k[None, :]**2) * (k[:, None]**2 - k[None, :]**2)\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:202: RuntimeWarning: invalid value encountered in multiply\n",
-      "  oper_1  = - 1./(k[:, None]**2 + k[None, :]**2) * (k[:, None]**2 - k[None, :]**2)\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:203: RuntimeWarning: divide by zero encountered in divide\n",
-      "  oper_2  = - 2./(k[:, None]**2 + k[None, :]**2) * k[:, None]*k[None, :]\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:203: RuntimeWarning: invalid value encountered in multiply\n",
-      "  oper_2  = - 2./(k[:, None]**2 + k[None, :]**2) * k[:, None]*k[None, :]\n"
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-   "execution_count": 9,
-   "id": "2ba6da86",
-   "metadata": {},
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KAN6sTxL0DUENoqhh0vp3Vue7wrxkXs02O2Fnai7E+7UjNKMA5kdEzbYtVeOxeXtAnG1H2kqJRkMuOfWiHbxp/dqf0Lp3NbdBtemq1DlTliSdrN1liqb7CJbWLCLNjXrVyXLqIV76dqAcmDuzpWW22KQ7Xm2pWN9LybGWyt8C4oFI8yFSbkk6Wy8abPYIo+PWSgOwZ5+BGgI9nLc/zLMv2aQWi+QALu30LN3GEkhmjs/m06XbEQN3DtjFD/lKjXevyd8qJLZKYL+qslS8EI1QYY6jlhAPRgeANxsgIqhz3zcEoRPQQ/XFzr6ZMC/dCaN1xsrscXxLDmjp/IooUePxkSiF7+NM5Mt5EcYyO7sVGZGzzbrvP5F5flvQ6PiJ5WXqpOUU3/lJ02QCvCgKGVv/hqCCSpsDvVSdh3y0QPpdYB6YV6XK7ykyIN7qRRCxckpgvmtkXXFVqPEcEO4N8YgfXq3CewO8gesBtHjWio2CxmRdekhXeqiuXHUeqK8LzFPl1UYK/AdyqcTi2PsNQRJL51Sx55XdZl4niIeO/14qXMiyqgEeDbeN3pwRWhTeU6Wnyq5R56HyUmXUwlxosWSr8pJgyqq+u5MsfHQbeyspBPFkdSr+l84vgHnMkhGmkwS77kuKbKXGo/tqR4hz0UOFZwI8K1rzlfzxirwV2CtUuqjswvmngXkqPzNPfLkLxE8W/vwDItefTqWXgzqdNleZH67KMyxCPv/6tdhSIXFaiMeiB8BbczRQjsxaaQH2zPyiFVZxdg33hst98+qdtfRJh1wczBE/ssd6l9wsBDm8w+XGPfh45ryVfrpb9Wv2scgVZleIB47PuHUaKEs6H4X9ei1YKSxj/xdL0PyC2APofJ5+ME/Ww+VrocpjeXZW7DlqPKSO97iz06/7MFXecztK9q0W+3BgWhbEmTgdwEuikqmXwmrdBtDIObho3lSHUqA6trxQWYafZ3eEzX5i1HYvYepQxsvL1UOmbdOTegJtFEUqL9suZhk7RbBp1EMXQjxaT2J5TGysscLGl1bKOHmcNJuNOU/GjhdJJbZK7aV+oG73ijNdr0gIMfWweSXlpObZstNJxGU1zRcIbS9Jmh3LpWcWYR6xQi+oJ2i1COoQ75DB9AIl1FuVi+ZlnmUqdqwciOfcwZlKW9rJGq4wM2/pqKY91LgU4oL2dYG4RIVHotmgi1ieRqyl7NahGU3gXtLwVkAv3KA1vnlyx5RcUnJpJTAP1ZkzfycJ6UAxosa3+fiyaiBbPuSQ/qDLsNNKrNmOzPxsiG/yJ+oogXjED2ejUMABHQHeCN4pNic98mZgPyPQA/OiHaFcGV7e2Pxo+prOz6pt08hsbupZG+/3dn5LaEpg3hTSrdZVq4dkpeZHriC7QdyL8HEZKCM1DzsAvDByuZvd2VkN9dwzVEugZ847Bcy5KFHllcPTaseSs0sVUOMSiAfrUUb0F8srrTukypdJwVbKImudV2zzLJvOK3dPiPNtCUxPzOsC8Er1XcPWqs7OTT9g7p5L86fyCtNGO0WNl0gwj+3LshPoCjBu3k0HqjefS7+mDXR+hr5zZXLzA3VH0+zYGcqFFOL5b+2Z0nMdn9HOzSPCtkUEWeG8kLJNfi+DuGhkSs6olAqAJ6P2BCqMlodV2+eR16j1xiq9ym7xywpe0kWsEJI3OD+6Mwo8y6UOoaIqfaxow0hZGEHFG8zbyyMPK/NYG0PtbBqZqjmWP3lFJ71a7ADxqJUSakMNxBsziG1DDSMj7bg4Eza1lpfviNWccmKqOTNtVJ3bGS3Uua/Mvbyu2vbKJb835afUsJNXwWwukbbLECyjofLucePLFqzxtobaEFLWnEL3lXmLaKruK5V6UgBEIC4VKE2tlF4qPAfeBdEU2oHo/jxyoPAslFOv4Ewc3Jgt1Hmub56rXvw8CYUuUuWdRWMyEio47pnzjc99+TI/P1xXrE3TxINXqq2+5gYdwSL0hHhLFV41EKIkna3XFDIvVK+g/vLnkVecnYqhXpmuCOihnYSDecJqKToASi2WSDpxeGDIVpKCjcxbE/R7GuKld3nK7+bkYR6btk2Ut/KMt+6bbEenOWWWSjOIM8dLVofmiQFeHBV8rXuMbSXYs6EurasW6MLySnzzpjBn8wkOfD9NLjQy4SLinAj6PmDTEJW+DahkqKEoTWK+2WyLRI7QtspQ46ylsjfEvQiq8BxxhQYAz+RZk37BCmFs47IU0MIKpI3JLC/bU5e0O5FGIbD+QvnMdtpmdIr9kRjRku2ZcyNZaF6mbbF2twxjVB74ImnDnYpbiAfLj9VNwve/ff+aeuTu98jVybzRevjrRcGB2p8XmrYDxLNtlEAkAZ6KTOVdHJXADpUXfvlyiwoKyytS6YVpuqnz3so80kaRKg+VsyN8pA+g6nVzUP64cdkJqHtU2C0l9x2cGeLF/V85aWxdJcp7J66GrRU/Q20jCsrJumzpBfRQHinM/cvYIKTD5Sd3eInqCh1UqQOn5GSQGRaQ0meJc3ljZUvSxOqItaN4qGHRSTY1PyAepPtFap8WCw6/XKEfniOcsA/Auw/UkJaTKC/vhiC/oFIVQssRliG2XiRlm/B85SWJ5mGm5VotUpuFLYudP01jhyPWxI43BoVUcHLUSMb0ra1inOnUPglZLN2j9dDH2MnbBy8qIO6kqwA4E1UWSobyzo5WarswDu3s3JQhjGYqPaHQg3kE03KsluiBwKZJdFYteQIdYn45/vwIQFrf4Sj1tVMjWXLtlVCe3BNHj4iuY+k28+ZHLZXQvhVsw/r1FBCvOM6d8vdW3i34OYduun/WNiwzr/iyp3BDZ9ktzLQmMA+mER6YNSEBSm4EbJSYVVE0pjzwx6YVwtyf77d5SVtst6RHnFRHbB+R+OKtIC48hoAC21M6HwXWSSu+Ndqetu2a/qgaSsPFAVAXlRmbz5WNyI6UmLYLzLm0vhILHcCp+aFpmVH6LJTQNFZNI7KtEmn88iS37aeiiYqPbY/lU6jGuW3MlLELxP3IAXioDDpPCHBR7MixVIQ4HfTIuYWssuz88nLKonkT+UReuk3DzY/MY/1zLr03beObG3+Gm5b1zINpZu+apvXbbf1ymyaSdl0GxhNnpwnKqghOqXMALyp7/nR2L8YP7/7QrIQ6jk4LleVDPJq2EcQbAjwYBUIs2J7SenrkYyKnvVmdndxxXRwZcGbzSUYW+ADNKSsB9M065oDmTXMAbBsWgPnSbgnM/fpygE3bIVgGYIJai+F2YYvCnc7lWX4z5ab8wtEHDsIwX6fZ5TbLuHkK+VadoOwJI6rKhXVuVPw2SQriUTD3hviZAd5QbZfGsY+xXTLSQtvn6QH0LHVeAHMnbQrmMaU8f2apciHQQ9EK9DZ8wINpSk5nD01roe5vTx/YraL+GeOC9L4aj0E8NUKlB8TPBvCD4N2yf1K3HOLUxGc33l9uHmH7sssJTGd9PD+t93vTBslY88CBts5n/HImfTBYvz1xeU++58Au3oHIq3Qnrfc7BHHJyyT8vNxSpK4c3LRsNWyYwLpMr/dIuk2+2LwCiG/2bdeWiafdtifog6eOw8ByiflTw5hCtnXphwQAo2ZFzu0QDWpqotgzlHdOepFKz1TomzXmlxFS3LQhMd+c5mfnexbJpr5CVR5LVxlS8C3wJNM4gEuHM1KI2nKoOjeQ2yVdPfQQZEPpFvj6fpj/WQjx5XsnFV6owEW4yt1Gldu0KaxtBPbHsLXSAe7VYC+FeinQY/UxZYvsFu93jm8eg/kmvw/r+XMDcy5vaBrJ49gnjUEf9MxJGgrx0tvzbVhYa2WCMO/W8UnKcsqNQDM8bfpIWiqxoatOObL2BNNxv5EJ8MS6bg7wim3bHNwZgMy8s9OXoe3A3hXqgrTJtoROCjlAD6jzzcmkAObFnZ/SadKoyCsFcgzi0jJCL5CgMI9FlXdec9hweWPTIhCP2XYSiOeq8FYAf7PwrrC5K+/sVO5fRVT5R4b8SdMK2pKVX6I8/Lz+jh5SPYZJEzv4EtsiPq6Yrzecpmy7p27DD6nxEMRL7+zkytJenXFPvO7KAEB4fYrWv/sZHW5IoivEmWNEDPHI8ZnlfacihxlMG5r43A35eWGVXE3D/Chc2mIbRqrUM1S6WKGXqHMvz8Y3L1XmUoslFE7ZfDt6Rw7EaehE+0Z6YlT8c1SsMvctlikd9htXHgI7E1JLpSnEW6nwGgUu3RYF26yZ4m44qMQPZWZrhWtsN7g3APveUO8CdD+NB+qlPtoJ2hjmTr0ScHsQ94cZbp5L7nvuGxuEfpcr25BCTgHcT2eBTh+YlbJMip5RDmx2Hr+OTd4CNc5Oq4V4jgon0R3gZ4d3J3CH2ia+s/NMYC9qWy7UExcXrB/t5wsAvUqdkzRVMAdR5SGVHYI7+ztQRmX4apyDOAfw0MnAHa0yfVKgU5j7qjyv4Sa9Y27AqMK/Qw1YIBwBfA7Ee6jwDIA3Ud+ZG+sewe2HuLOzm2pvDPZmUC9V6QKg56rzmNVSBHMnDbFYJKqc/a02263kpqCQQpdCXOJR86NV0jCn82xbcxT4VJ8gXVT18mBnH0+7B8T3AvgZ4d0B3DVtOsednbFCMpeuK9RbAD1HnbeEOVdPoD42beB3FrAZ4EefPJgozkKcA3joJiE6IoVaKhTmXNBt5dsvtXd/Rm0V7jc3PQLjU0C8B8D3hPfJwO1HFcj96KLaK8CefaJJQT0yPwr0UnVOvm9881yYr1/iFovTKK8e2hB/fmyZKyKkxjmIS27TZ2/PX9T3BPOYKq8OAx76nK0SU+MLiCOWCsoh3luFBzdVQ3ifCdwtoc3FhV0xDZehOdwrRsZkqfWICo/NZ4EeUudkGgv0mDpnOkFZmDttZmAOmzdgsYR++8szTzeQvYiZRmoseArim9vsE/XTkSnABPQUzGnZTdR4CHgZ6tyxVHwoh9oUgnimCj8rwIuAeWfQ5tYFr8h3hntT1V4A9WgbpCq9BughuyWiztlOUA7mm+kezP02bKCdUOXAZK8w03Ni86KJQLoYxKUnEGqp2DI4mG/ywdsdFOqGIRoV9s1DahxeI7jvIUslB+I1KrwVwAXrtniXawjvruAWli23VjrCPbQiitZ1oWIXqfUY1APz2HJ9oBeoc9Zq8efZwmIwJ2kUIhbLlIBZ5jTAzVxGrlJPjRv3bRcuHxfUUgHgjlBR8XHlOWGMkh2HPriX6XB3RqK8Fc3jKHIG4j7AEUlP53nfcwF+Gng3gvYRSlsadR65X3HbK5R2yj1TsTeDekqlC4Aeg7ktM6S0FybHYL4pT3Cj0Er+aLqpWLlSZ9/6Q6ZpFYe49FG2m4dkeV64UgYaajOShbYJgNxSsco71TwL7hDUbf2B0Suxzs2mEG8N8JPC+8zg9qNpZ+felgxQsL0yFXsW1DNVugToziRPQS9pIko7CXML5MRJJajK53kGBnbEdYlPToOrgg4z9CHuKHdhHQYhj3xV3loBIzyIo+74MxbUC9wDLebm+ZA127ScncLbJWHoNwV4hfoW70JfGLS52HZ2NlbVwQXoaMtUwV0IdbaeTJUuAjpntzDq3IUzNlZLEOZMeUGLxVkegrTW+wwmyEaHJiYgnhp+SIGcslXsb43t24WahIVyFOpzOzb++fpVBHGhHx61UWoAHgFaFkwrtsMZPO3W9WwVeW+wh+ppWFcV3P2EArCzZadUegroKbvFV+fKK4frBGXSO8MSyfwF5k7b+8KbC6UMq8bpdwnA/fn2jk1gVeerEo+r8q4RgXrMF4964h7EeZuF1OO3h/vulxNIk5weKmeTv2z9vwloC+pKWysdgSuqq1GdxXAXgD2q1EMqPQV0Tp3Pv1l1TudTdV4Kc0zgMCFwOwVN3zf2SsiKKQhfjfsQ5wAfinG2UOx3uxRaGYxAUJVXhQFvq1Bwh8BosPXFQxCfIwnxlAr328KVHUsfmhbKv8mbv967QHtPWFfUWeaR7wn3WJ2V9RZ1pgpsmKBS56BeAnShOi+COdcmp/xFsouixdBEG77d4kM8NZ6cGz/OPU+lqY1iAkMMg+mx7jgU2OxvBuImA+KZKnyzCXMUOZd/kzdvfTcF9xHAblhvu87ODqDdu95s1Z5Q69GO0hAsybQg0CXqPBPmTkWOgxIYxbJMonnCwDZz+cknG2IFtrVVuOGFIYjnvOrNQpzC3B9muIxgmRfYAj7JpFQaTo0HFaw3n8Ie7vRciPcGeHRzZ4C7GbTvHNihuER93hYRW4CekG8E+Cy4R9R6EOqMIt9aHCRfBOiOOveKNRT5DMxXse0p7llROxYLB+z5hLAo8JBqj8A+FnoBu3Gm0c/QnZ5+cKNUNh45UK7KEyNRRA/bmsHNdm5SOIcgnqPCSwHeCd5NoH0EsA+o066riz/Bxi59O0eo+AZ1RpU2N0MCdUaRc0APdojmqHMpzGlb/Pb4ZxXm6DNmPQW4zy13fy+LLTyCrXIGtnZLzCv3OzMX8MO1WSStCPnnPqTt+PGg1+4rc2D97aRz09RAPFuFCwB+GLy/EGDbCK0n8fPIgZ3gDshWVOu2FAJetJ4iFgx7ReSrdIaXYnUegznNGoM5IhaL32ba6emfsTxrI+cdnaEnHPoqPKbGuXnrDUBb9a2cM2c6NrBmfm86OSPhWCopiC+/hRDvCfDEOiuC9l7wPBDSfuSspyyP/FC4byoWpGnRNq6eDLiz64dR61GVngt0qs699jugniV5EOa0TgQsFr9y74REbw6iFxGS8P1x643rhMWiEzvHiLClArjqfLVZFG4ZB5bDQ25Eig/0kKXiAV8McYkKLwR4d3j3gumJIO1HrZ1U3dkZasBhgKfRC/YZcE9aVnZCTKXnAp20iVPnazEJmG9UNQNzP+ZCDMxqnxCCUyVe8vIJZ/EI0LUyDsBjbwjSpP0U1q2eKe6UY7w0HNRpWgpxZ55KQlyswncAuBhMreB6YkjTaNZp60XbW/RJpBp8CtAD6R1A2k4h3INgl6h0mjdgUS/pQurct1okMI+CO6LKiZ3iQNuZzlssoZEqVo2HIB579sronERmoHsw1yStVgY3bwQL74tTcCsyHez0oBrfFLzOL4F4TIUHAV4IbxGgaiD2hYM6FZcNHHaKnAU+FPqxdqbaxSjkTRE+rJ0va4KoSveAHlXn3vbOhjkiFovTtrXMxV4JgT0RMS/dh7jEI3dGrRCYB+sW7oAcuB1bJTICJWip5EI8R4XnALwE3rlQOymsj4JzMki7LqEZS5xAOdeuyG4nglC7QvUlwC6BelClM8I5pM6N15YV1li+ZcMc20zOzUBz/QaR1cOocx/MVI2HIC59CqK1UyzM7TS/49NX5ratoTD+F0OGHFI1TtPlQlzih4dUeADg1fCWHqc7g/G0IM6JxDLk36J/ArDnRs2GLDoJSAEfWbdRqHMqPQZ0v5rFr4YLa6KuxTDnGkEzU4jPKpy+eYd+xsLaKuw8AnZE0nER8salzx+3ebefNoH9pMrc/hHbpgHEewE8uDpbK/JIvAkYS6NgWfM98lwVeuch3YFEwE+dFA0/b6vCeZUeHMFi53t1+1aLr8mTMN/U53k7DLydNMpELZaQd07VeAjioZEr/oiVaRqgyaXCuKxMry2BjbxCWzmfLNS9NNQOkUI8aaX4AAfcOsDNbwDvAgB9UYDmotHy979F38YbBb2Nos5dLk9QRm/rcaAeAjrJz/nnjjonVUVhTtq49cvhfbd+ClHm2O4OMaDHnqXiQ9wCXKuRL8zopX0+zOlGorD3bRXaZv/7MslR4owaJ9/9USpJiJeocAHA+Y5NZlpsuhcPUO9TTbdRK5u4lw3a6YTD7dAiuHNg96Duq3R7byIHdPY8QdU5o74dmDMFLzAn1sxGlZu5JGMWhU6/57yIwh9qSKdRgHOjVpb5Ri8wX9LP7c25LZ/aMlSB205O1hsnapy96acE4jkAT6nvHKDHyukZ98KTneKwUSunjZY7SGJ9hnZ85zjjto83LaTSc4Huv0yYhbk3fU2rYAyBuT0rLJ9YVbkzesWFeGj1c89V0cq1WSykU175AvQZ5st0TG2zKjykxjfco2k2o1QIvAUQpyBmIW6BTRti8gFeA+9iYD/g2zbI+oyPWnmAvS4kOy6zjv0DxXDUtXkDUM8Bug9zYAW6A3PLZM3DfGurzJ9ElVO2Kw/ok70SXmnrs1HWNBTiG588SZwV5svdnTAYoZLDDqf2ugA3cBW4q8a9dbL5W2GtRprWhXhQhZcAXAJzP08oHpDuH5F1HLdWHmDvH6GNQ9a1COy+9+1UEQA6sVE2xRF1rkgZgAEVsxTmy4so7EnEwpCo8gXWM/hg4h2efjh+OEMYxzMPXYZga5/YPFaJS+0VY0CsFGutWCXuq/CQGmcg7o9MsdtJoMJ9gOfCOwruB7D3i4x1neeRC6Bzujj7jhdad1y7PW98Scooc6qO11ErHtCZ4lmYW9Aqos45mJvZYhnNPBhbTcNBbP2GgInx26UvYKAPyqJq3B9bvgE9vWJYwlXl0huAls5NAvClDrOut+VvVEt1yqh53CNWiI9CKyWiwsUA989vofWec+zc63F2hmiw7tp0duY2RLJSz75jtIrUcob8cjJv65HHi4oBfbE/aB5WnTMwnwHu+uWkUbQDcJ6vAMdWMUZhxKzuzdQgBf7GoOlzC3E6zw29rkcP5qMZWCW+rLPZShmJpeJ0dMJT5r43PicKKvEAxFkVLgV4LrzfshJv1f6Tsmu/USs07n2nQEWHjxdJ8RdR5hzYg1An30VA939LYb4Zh0etFeOqcs9eMbGzELajVajyphC3AB82G2lcclKYj0Yt3rgtVysDE7FY7MnHhTc8Ne7B3Pnj7RQW4r4KLwS4qIMzNj0Sux0PR8dJ2XURXkm++ThqvGtOvcFOT2BLXsTFvDPfqMnS9oC+UecSmM92ihoVjJ5pRC0WTpU79sr2ued+2zdjxz2IW4CHPfL5Rvx5+SYlvpZ185S235ZQJ+dWjWO1VAygRrVMy4G4r8IpwFn7JATvTBV+xDGRW+eDXdM6u9gvNt7qijkK1ADkZ/HEug8tAytkvWkSqDsKnZzgl6IMnFEtSidgbohfvkB8q8oxWyrGVoK0OgdWW2X6vkKc2itOeswKWwEW5vamH60meyUW/pjxZeRKTI3PVS2WSgziY1yFswqcAXXTzs1YNNqvayLV9i+FZxtrJThC4g5iN1j3qienXLJdkp2foaze1diqwFegOwD31flop0/q24G5BZOe/XLroStsVLkhgF+U7aySQ2h1vHBsIR68s9OxVUZoo5bb9nWkt3WcZ7mWilXonhof1dyZqWYAq6Vz04f4otJDKtwBOgPwFLxzwd1j384tsyFzYsv6ltiW9MjPBva7h3WrkIBakJxzayjQp+9mBbhNaxW5BcnowdxaKyOmzk/7MJPprhusj7adIKgWQE6fk289ffow998OpJXZQNy3V8ZlSV1bZZzz0bcE3WzKeRr93CpxosZH5YxGWUDtQTsI8ZGsfwfoAoAH4J3dqXmGiLXvC4F8LueyOzujl/cN4hAL5Ow7dm74y6M8+4zJkgQ6sVsWdW4V+ZwvCHMLIHsWmBU4rJ3iqPIp0TR5vbSwQPdfHOHf0ekqc3K7PoBxuZOT2iqTKqcnB3uCcVap7Zi13433uUCZXLZQIFOIj9xolbCNIgJ4DN5vaf+O7bwNYy/LphXvmo1aOdSDzokTtfOokS/Km7fwUq3wprbLNG3tEHUUOSnTPn98SWdhvpwKzPQiznGqZLGrZ8U/qXLjPYxqGvLnj0DxrZOtvTIyPjm9LX8C+I2sjeW2fZqDDDcEVktlHXGDyUrxLZVxVeMsxD0/3E5b1jcD8BC8a8F99yNOdoK7U/yJOAIcNfxwzzhwhe+1sbPVQwDshs5XK2h8oENNP1aPfFbqelbperIZojA3ZuKq9cxnhlLrwu/w5O7GXGwVYq9c9A0Dth75oICbMriOw2KrDDCLvULDr8tvl1XhZlRLf8CiyKUQd24CEgKcU96J7X/a/bBnMFelbzneHsgPAnf3nv/SUHzbnIOKKjtilfgqnY5iWeS0MmS0CpxO0AXdek4/Gig1d36Oc/4RazmOZTEp8dEQVQ446tjGosAJxLlb+EczN04D13FYbJXNuvE88dH4/vicZgE3UeQGpHPTg7jf4WmhHgN4ylLxIrgf7rCfJZOk9sOe8cbBvj798F4X7F7AXdDOFkoqVMRGpHuyPGyxzL+Vna2gRuN45+sbjOf5S4/oNEZ86fwcp5ZM5alZ5WuMaoRSClqvEA+FtVAG648TiG9UubJ3do4YlcIANalxxlKxsQAcwDgqjKOCGfUE81mRw+/QpEr8Nq1cRdT3OuyQgTgD8Bi8pbZKk30pxgjpjubP9vI9wJ4Z83Jc/AmnX6B7sUoy0ja59CVqWlS2cQ8aR40HoG6dDsdOWSCMVZ2Pq9UyWSYz7O3zV6xWt8b6CJi5DKONo8oNAamvxv27POmt+hbow+yl3wzxfWx6Y9iyMNdl63T/Zt4uEMeizJcRKs7oFALxDcwDAKfrPQZvE5gujcA+E4qigQ6ZwHQ65R9WTDi89m6tlTMt0IHQtiE+OITpWpdXk0f5B/IM96WNFOwGG5XOAh2rOjeYuTmrUtuLuTxkS5FKbFmjgsGkysdR4aYUtCFDAL0d0ipxqsaf1A3DbLXY0OqGUSloY/CKAYMZccUwd5BqXEmZI6ytM9kqN6NcNb6ocPqHBeJqnJT4os6nQh1rxRl66MPc25bRadjOy4rcfEKxEIRwBl8OgzrAr5cTszDv5cu9F+QE4AbawlZUVk+4S8oMKHMH7NQ7J+k2QDdqslbsghtMw7bn8eS2hGkcOWAWI34+WEe1jk701LA/rtsPq8QtxCnMx0nuA2qcAK1UcJTKsmpo3dZOIZ2cFOJq/r6BOLFSqEJnAR6Bt7MftYJ4KrjVLASc2DIR8uVQqC8Ve79PxMP9H2N7Elhz0QrgTeDd6iQhCc9moXDfqHDfZmGAPmUk6hwIwxyYnq1iOz3HyUc3SmO0naOaKuTtzmZHrdDnrlhVvqTBZJ+8zk85tFbM9sFacOoysxqfPHENY60Tq8Ctur5FIL58p5YLWX8+wH14RyDeckRKanTTVCGXMTEf5LwusWGE9sthQLcRW/c7M/GYx9ieKHZT3xXgTraxwfr37RTQg8WKZppGrd+Nzb+o8ln8WnVujWUrfg0DczpLqWlQy6iglMbNjNCjws0BuqukB0zWypO6rdaKGjHMJd+8I2saBTN60/RS/s0o3EY12yqaWCsK5jaBG6OCunkQv5EhhoudojxVzgCb+U63QzMrhQt60maCG+Hk55XOFynre1LpodiZiW9v+KEwTgHwEni3uBqIhafOqSIHiBJXZLq1Vvz09mFZ2kp6EN+cwFxhUt4KU8fnbbZARg01fxo9euPLV7+cPs52UJO18qRuDsg1FEZis/hvEbJlbeycBeJ6hrhehhsuyvs2Q5tC/EZUONPZuaxbA1d5C6yU5iNQEso7CswUdCMq+02q9IPiiwP5bvZJAYhz4V11BRAJ5R+c5CChqnwZlmih7gOdwtyqc0tzTQunNwxNmc1tslSMmpTwbdS4jQbXUeNpUJtOT/8BWnqG+TIfwCsmoOtZzW/GmWMq9zrquT69qnCqxG9Wic/wHsmntVJG8pvaKWTdpEapRH3x0oio7yDcW0BdAHS2TEF+rqwvDehfDMjPCvAceGer9BYHPzmAHGvFzB+ezYLZK1+mU4VuJrvFWKsFcwH24LOFXqdxi0YrjErjdjPQ2uA2Tpo65JdTNf6k1huDMOex7RyVdvxzeGUaYLJVRo3bTU9qnEAcI1aIX9Wqvq0yXzpAt1ZKaIRKENotL9Gph+VPx3b/8oeh0rR++iDUM4BOy3wAPS++CJDvAvEWAK9NW6LcI/n8oYnLVwJuZ5SLVeTKVelGY74xxv5ZeJvVNyeVmYsBbgpGT8MQtaaqfFbKxMu2sTxvBWbxy5dx5PMTD0fo5S5QGzcC8RujxsfbbKnMEJ/gTSBuob1R5fOSsbfie5YK+cw+YSdgxQKZ5kuAOkeptwR60nIRQDpZzhuJNw3yewa4KF1pvljaRD7HXgGWg2kRvL4iV1ifhmgwjfrQmB+BO93haYapKmqXGAXgChilcNMaSk+q/PWmcdEU5trxvIcZ5pMqv5LH2a5AH+bx7FqZecy4XiB+HTVeb3pR47fbrMavc+cmgbi+zSp8HqmibliVuIV1RJE728Bb11k+eEJ9sta1r84jUA8qbwbGLYH+UOfyeJMgLzkIisqqtUUaAVySJwfwsdiUo7afG6hbn1yBjFyZ/4aVKJOhopxycNUw2uCmNbQ2uOoB12HE1WhczYDRTLfyTE9IXG8MelJXPM8dngAwzBVPww8nC4aOS7+aYSpz1LjeBg/iOg7x26rMLbyd7xy8EyAviRxgb+Acg7pUpUuBzjY0MB1t1TnbpjcQbw7k96rCmwA8c364vXKqmPmB5Gr55ylyYFKpegXGch+Ob7UYM49WVMvAQAPAXDWmodoGt2FSzK+3AddhUuM378icLBXjWSsGN2g8qRs+macl7c2sHZyvt2FV41eN8aphrpOlol5ngL+qLcCpveIDfIQDa6dDk6zmknWeDO/qKQX1jQVTAnSvaSyED1TnwTbdebwZkL8pFZ4D6Bx4b9J6E3JORKGZizJfOxedJyJqrM9j0ZhsldH+KYzGAIMdLmibpWEUcNMG16vGoAe8jrfFCrmOw6KuB5i5w/M6WytTKRoaNyi8qmEZkjgahes4LKNUXmc1fr3OavyqgVc9QfxVQV8V1HUCt74SiBuEFflGjVsiydexD531IWReuuig6zTUS4H+UOfHx5sA+b1CPFeFxyAdHaoWUn65Cp4JdhkUpgGFTifoDHZGkSu9vAEOeh7VMlnpyj4gEUZNnZ83a63cBryMA17Gy6TKoacHY2Hywxeg2xe3KWAwZvXKjcYNk6J/GS94GYcJ4jeN23XA+KqBWYVTiOsrnE5OTX1xZrihIiN0Sm0UZ7QQCb8YRaYY+7Abm08C7ZhCjyjvanV+EMxFZd1J3DXIWwI8WV5viBeqcOmwNU4Jik8MXPv86dzlMO0IVfPt+vOTDqk6n81xQAPjrMzViEmdW5tFrar8VQ/4PIx4vgx4uQ34fLtgvPj2yhVPuOHZjiU3wE1dATwvaUaj8Pl2wcttLuc64PV1wM0q8eukxvWrgr5islWsIp8B7oOcwjs4OkW4/jbTPeiEnIkJ1GZe9wo+xGmdDoS9tjiQK1XndwJz4L6Bfrcg/1IgXqTCOQWeyCc/IWAbW2nI/l4frmVghyUapWAGQM8gh8H88uVJnYPCHHPHpxrwOhh8Gm54Hm54GQd8Hi94NdNrmgc1qfHneeSKjVcMyyiWVzPleRmnE8Gn1wteXy+4vQ4wLxrqVUO9KOjPLsT1DcunA3JjInaKYH1500IAdYZ7UphRKDtFE6DbmQEV3kqdnwrmCOfPLu/EcZcgz4J4bXlngXgpwMl0McC5ukrUOjDbLHMytf42CnMH6PTKOKPVoszNAKjLpM5hYT7bLEZNHZ+vg8HL5YJP1xs+3Z5wHQe8mmF5psoAM/vk692dw9zJeYPCq5lsmU+3J3y6XvByveD1dcD4MgAvGuqzgn5R0K8TxPXrCnGqyNVo4h2bwnXkrE7qZxP+suvWhzenskMKvUad3wvMM+NeYX53IM+GeCL9m4a4BOCCeVkK3m8DVjWoln8r1M2szKHml1IMgBkUxtsEc3unpLLP9Z5d7pse8FlfcNEjfnx6wg+3Z/xs1MvDtPR8Q9B75zb9SdePRuPzeMGPtyf8eH3Cp5cnfP58we3zAHzW0J80BqvGXzH9XVclrm5m27k5K3D+xLddF+7KIqvSAtVT3XQat6v5Aj4MeVOlzu8S5pG8ReWdMO4K5A+IB/IvcI2o8JjKTgE8+Htb36adgNMJB8AZZ768GchaLTfADGYC+s27c3I5ujRGDVwHg0+DwcfnJ3x8esaP4/Okyucx5c8Y8WThjWnazaxq/OP1GR9fJ5BfXy7A5wH68wTx4ZOCfoELcgtwp00A9cW55ffXhQMJon6NUiuwCUxSNvVShiIQ8pR2VJ0/YJ5f3snibkDeGuJFIS3zpBBvAfCg2hcqdYAcT2pK5KpztQ5LHMz2hhv7LHBojGrAizb44ekZH55e8f31GZ/GJ4xYH4r1PA8/fJ2njdD4OD7j++szfnh9xg+fn/Hy6QLz8QL9o8bw4wTx4QUE5Ma7ixOTpRJR4bEFt9YSnWYsYBeIqyTAN0D3p4cAv0DZdIf5JqRAzQSvKN4wzO8C5D0gXqTGc8uRRM2y9YK4FOBsOvvduPP8tttwrJb5pRLzaBajFfQAjBeD8QqMy9jtSble5yeK/6jf4bvLDV8/fcD3797h0zh54U8Y8W4u/8VMQP80PuH76zv87uUDvvv0Hj9+fIfx4wX6o8blR4Xh4wTx4fMM8EWNY/XDFyVu4hD3LJNpGqE5Ud5Wia+QNlGgRyEdmF4Cc1HUKGVhmlZ1vVWYnx7krTs2k2WG5vVS46G0ITUeK6cC4nGgmzDAne+Gnw6vrEBQZW5HtYzDBNLxqjBezarO57tBrxhwHQy+f3qH757f43fvP+Dj8zu8mmnXfiae9Ku54OP4Dt9dv8J3n9/j+x/f4frxAv3DgMtHhctHheHTBPHhxULcLJ2bajTrujKpZfF8keXTEHCrDcQ5oNsbfSjAHbhXwnxt9HaaSJVvFt4tR2KxSMqR5O8B3nuA+elBnh0dwB+Klmo8y1Jx5jNKOfK7FOKh9JwyZfPTe+6Zdq+Z529KwQwGgwLGYRqiOF4mu2N4Aa6v83NPbgqvuOCTBv7mcsPP3n2DX737Gp/M03Sbvh3Fogw+mSf89vo1/urTN/ibHz7g0+/fQf/+gqffa1w+Yvr7ZKY6Xs3ii+vbvAy3ULvhtBsA1LxCpo5cbJW4mtabnRcSxNP3VTWzahzkewHM2Q7QELQF00tiV1hWtvWMcWqQf0lqPLfsqfyyAlk7IAfingp3vGKqVC3AzVpWUMHbGM3yRiFrt2hlYAYFcwGGi8LthYwmeVVQRuMFF/wwvMdv3n+DX77/Ft+9f4+bUXhSkzd+MyO+u73Hbz5/i998/AY/fPce+u8ueP6dxtPvgctHg8uPkxKfIG7moYZme7Ja2jgvJrVNFJHLlroKgDYEkGq58piXFMtLNbAmo6COwXzZfhTSmeHAfFkwUn5u9FblkfgSVflpQV4E8begxkvqyFTjbBr7XQBx6oOzEA8A3AEi6Syk9U3f15c+WLgsnaAXjcsA3N5pDJ/V5GVfFdRV4zOe8ddPP8G/fvcJv/n6p/hsBuiZAp+Nwm+uP8W//uFn+Ou//QnUb5/x7m80nr8Dnn5vcPlkcPlsMHweJ+V9HZdOzaV9TpsM7KgbBczfDZRWxO+flTkButFY7BJXPNsprihOwhyMEvcLybVYmAiB7DBVXquqT3KCaBWnBfmbi0JVH5qfrcZD4J7nudON2w5PiU/T5BCffm8BPo38MPPb6FflG1rGZaiiVrg8aVyeNcZnjdcfp45K/arxI97j15ef48++/iP8+1/9GsCPAIC/GT/gz374I/z6r3+O8S/f46vfaLz/rcHz7w2efhihX0YMLyPU60i8cKZ+YL5D1YJaAfMdqtAKi11CLBUH3vbZ7AGYg1gcFObrtFU5s7YKkA1pG2zHJxcd1fQjyuIB8lbhcbWpLRQrK6XmufmMMufSbuC9TKuA+Ejm3YwHeLOCfhyXW9+nttEzzfQuz8tFY3zSuHy84OmHAcOnAeqm8RFf43/7yR/h19/+Ev/hu18DAH798kv8r3/zx3j9f7/Gh3+j8eE3Bu9/d8PlhxuGT1fo1xG4jnPb3LqAWXlrAHp65gu0mubpmd3UTlEzpvX8OebBXEFtbAiqwJdtFTbV3fBVuB8x4DaEcbG98ohknBLkvWyVrv54TtS2NZY+kk9SJqf0OaBvgoE4KPRnQG8gbtXvbVwAbufhZuE+Tr60Wf/s8a+1xuUy4Pn5gne/fcb73z3j+bsB/x9+iX/27T/CP/36/wEA/LPf/iP81f/1h/jZ/6nwzV9c8e63Lxh+eIF6uQLX2/w8ALvAav3TCtB6+j7MNBysR2JgoJcHgKkbYIbZ7TYKZlxhbgnmwHwQrFNs4cv62cw2S40qybUKROl7wDlUZqSuXm09q71ySpCfPXp0woqiYb2sxZKoJ9m56ZVBOweXk8ECc1KOD3HyidH+Hqff9nMcYSx8Z2A+XS64/OYdvvo3H/D+b7/BP8ef4n/4xb8NAPjn/8uf4o//J4Nv/uXvof/uI9SPn2GuV6fjUmk9QVtrYJg+zaABPZUPo2dQaxiMU/rbCDPo2eYw8yfxsccJ/NQGcdaRVJXTbRPoRGwKmYPU8llBefZ4gPzgCA07vOsIngjmGctQRONaJ6P/yUD8ep0AfrtN32/Td3O7TekBQCv89M8/4Cd//vfwX+I/BwD8w//299C//jcYP37ESNKpYQCGAWrQMJfL9F1r2ENj8akxv3R0VO6nUpNCNphU+whgiKjmt2InkOV4wPf4eID8EW83yGNlS4dqPuIR9xAPkB8cziNL30qsMtYJM6tXaAA3rCM/7GgNPUu75XMa/uGK2AvUOM62xzBNn60VdbnAfPUO408/4Lt/6xv8xX+k8F/8p/8dbkbjv1L/Gf74f/4JvvmX32P42x+Azy8Z1op2Ojedz3m5lt5OvS5rcN28hSDL8VDjx8cD5AXRDb4BAIrnZwRdhs3yBEGM+cYV43m6aqt47Sg2A0DPHX/GTp/fEAQzfQ6T16z07D1DwygzvfRYTzaG0drp7FxCa+AywDxfcP36GZ9//ozv/3jA7/49g//gn/wZ/uMPfw4A+O//yf+Nf4F/iD/4g2/x9V9+zXZ2LqUynZ1m6exUMIOdNrddgYwdV/PIFayjW2Dnc+tUkfy0nMCG86bTdE2BehCcHyeFsjglyItAKYBctNxQ/obwzCkzdx04z6wO5JOUuahmPx/C5QJTvctLlel9it5QPIzzqWCYnpkyD/6AWcbx6fkFE+P8xiAzJXLqmoE5Dz+8vb/g+vWAzz/V+OGPND7+/RG//Hf+Gv/05/8Hfq6nXfw/+cX/jn/17/4B/gp/iJdvL/jwG413f/ecNfwQ3vBDO3Z8ge9goaxImrmMBdRqWVdJWCoebKkRK1OaeLnJNLllemU3DeFJjUavtp71RHNKkN9leABtqtpj4I+p5xDY6bTQd/AAj6pymA3Mp98ezOcHXgEzxEdbyGSrTBzVU4ehs0wWggrmSeNmbwj6WuPlJwqffq7w4x+NuPy9j/jHv/gL/MnzX0HPXsefPP8V/vEv/gL/49//gB/wAeNF4/qVwvPv9TQG/fN0U9B0R6dhR+M4D8JSBNL2lXWaqGsK+BnaPsTFapwDuhJ896ZJVb54XmZEl+ERVfEA+V4hVfapdPN8TjlLyg1ZKu53OxZ6zbv41Mu0PJgv8LYZxskXN0atozwWuE9fDFZ4rs8pVzAXhduzxvW9wvW9wutPFF6+BT7/fIT+1Sf8yR/+Fn/69V/iF/qjbTV+oT/iT7/+S/yrP/wD/PltugN0fJpg/vR7hacfNYbPZrq78zo9a2UaG2+cNoG0aYHx8h0uwK2dkgFxur02dgytD+581mLJVtzkRBULabkPUO8WpwV5L3ulVVQrbtLWUFniOnxIB35z6puqbve71d0g3jYpah5uF4T5ME8c1aJuzUTmKa1WMOShWcstPqOZfG+4CtXYJyA+KdyeFG7PCtevgOsHhdefAC8/G2F+/oI//IPf4x9887f41eXv8E7dlpdMvFMjfnX5O/yDb/4W3728w29ep2ezmEFjvCjc3mF6HvmLmh6a9WpfapH30CwHogzAp/RhiLvT4E3zThqb+r19gnz6aXJhH1LzhquzMLJsi9qTREH+s9oqwIlBDjS2JyRlhk4EhWpa2okoCiZvtir325UEewTmc3rHZrHlUfVt74QZLUFsI9YCnSUgnrQZpiTTY2wVxgtwe1IYnzGp8Q/A9QPw+u2I8adXfPPtJ/zqw/f41bvv8O3wCYMyeJ0fwDUog2+HT/jVu+/wVx++wfffvsP31+mpiUZrjE8K4xNw+QTcLMydx9gq8hhbtd2OFNL0N1XgsN9perjqHdz8AMQZiJbCJvUu0ezw8hbbKicB7pkhDpwc5EWxoyqvjpAqT0135s8wz1TldDoFdQzmXtPW7/ZBS6QdK7BnMM/9lattsj0yNkpVK4wD5meRT6C9PU/q+fYeuH4wuH5tMP7kivc/+YxffP0Rv3z/PX5++QHv1ev0fs65ITej8F694ueXH/DL99/jd19/het1wCcDvOIyKX6tMD5NT1Qc7WveroC6KfJiCRW/o5Uui11J62rwQKwC0/3vYYiz9kqmGjeepeN80vTC6SWxKyhPDuWSOD3Iz6zK2XIqVLkI5rFyKmFui3BgDjijUMycaPPkPQDTXY5WmdvG0wVkAM4oU/qqN/tCifFptlXeAbdn4PbB4PqVwfjhhsuHK7756jO+ffcJ315+xAf9GU/qCgB4MeuSPakrPujP+PbyI7599wk/fPWM6+uA603hiunBJ7ZOMyjoi4F+VdMbiugLl52XLq/LtgkOetRCmdOEvk/pFDgAJ60SIcRD7d20O7Q8XPRW45H8X6IaB+4A5EABzAWqvAjmLdpWUdcm/QJkYrFUwHwLcFLk8hxsBui0TcuyKGxsE25ZQBT4rMLXly9Pr3qztsf4PEP8vcHtK4PxqxH6wxVfffiMb99/ws+eP+Kby2e8168Aphcufzbuy5ff61d8c/mMb58+4Yf3z/h8HfDDTWE0ClfotUN1APSLgr7Qly8r7+XLKg1zZnmXZfbXgfObB7jkdw7E2Q7OXHDtqcZrIZ7Z1nuAOHAnIAf6wDw7pGXmqvKQ+hZMz4W5nU3DUeOJ3/R51dPzRNxEi00TiY1tsEAcDsStLz6p8Rnk7w1u7yaIqw9XPL+/4ut3L/j66QXfXF7wQb9Azw9zGY3Cywzwca5UY8QH/YJvnz7hu6f3+PjuCa+vF3w2CiMuAOZx7M4JRcHYtwXdMMNcecp8PWuJl5+uZLtuybRqgMfSMvVt5+dN537v6Y23LvNeIA7cEciB9jA/lcWyB8zBTCPzkkAn6ZUhIKDl25/ccD1SmKvC5+8EnOMAmMtsq1wmiI/vZoi/G4F3N1yer3j//IoPT6/4cHnBs77iSd0wKIOb0XiBnm/wB16gcTN6eo+nuuFZX/Hh8oIPT8/49PyK203h9abmp9nqpd2GtEtdZ6/cAt0+y2WEo84NXXmxdeGtk2W9JKaJOjuj+bfbI5hHOJ37LYE4C8sQQGvU+BuGOHBnIAceMJfAHMDaAUqTRKDtLAtpz8Y6odM2GeikALzn30ZhvpEGix8OjaVz01ysrQKMT2ZW5BbiI4Z3N7x7N4H8q8srvhpe8U5foee3PI/QeDUDBhjcoPBqhmUoolYj3ukrvhqmvO+fX3EdNcZR4zaqWc9PpwCjAbxM6lwPmJX5BHRYi8Uqc6LQl/UNTGPlYxEDYERl554ApmkPiKfi3iAO3CHIgQKY15R3JpgDi6IGtkrbTeMBPZCPg7yzTLRdCEA8cUA6QLEQtwBXK8AXkF/I55OZFPk7A/NsgOcR+vmGp6cbni9XvL9c8X54XdW4HaUChVez7t6v5oLb3KgBqyp/P7zi/eWKl8uA69MAc1PzOyws0KeNoPVkr2gNqCvmxwgA+qZg5jcZqRHTwJ0Z5sYDurtCw+vLWWfcfCnAyfQagKfmnRrimXGPEAfuFORAJswTqjxZ3sEwB8rU+ZRGOeo8BXSbnzuB0PasC+Ol88pZ8lCAk5tkjMYW5D7EnyeIm6cR6nnE8HTD09MV75+ueDdc8axveDeD3MZkrayv4HkxA25G4zYvwJOa8jzrG94NV7x/GvB6G3C7KZhx+oN129UMc6Wmx5DPVxMY10/rmVO/fFHndh1x+1Bs/THTY5BMeu9+ebkqnGvn2SGeAeZ7hThwxyAHGMjFwgNSqLxDYU7bF0ufo87h2hyKFBqE91zf5uQiDQrw+ffmFnWNDcgXj/wyAdzC3DwZmMsIPI0YLiOenm54d7nheZj+3g1XaNL4m5nU+DA9JwAA8IrBUegAoJWZTgS2nMsNtycNM2pcRzXfibrC3CgzK3K1PIZgBfn6Z4wi6txslXnp1WQW1APw3qQTll8C6CMh/oUA3MZdg9xGS3W+N8yBiDoPqOGQOl/m0R0zYLlM2d0GbhZNcKIMHbzuA6ZcO8UB+TDNW4YbXsyqyC8GZv7Dk4F+GjFcbrgMIy7DDc96skc0DAaME7gx+eM3KNymNxwDmBT6DWrxyQc1YnLNDZ71Fc/6gstww2UYcLvcMI7TkEQzq+uJ2ZPdomZ1jhvm3+tyLtvEfs6doHYopuLG1+euY29dr+lUeH6psmfyJsvi8mSki04PlSPMm13WncSbADlQoM53gvmmTcyVgUidk98xaNMdM+R7r8n5A597jG2wjMBdgbGOTV+Rr8MNzQr0pxniTwZ4GqEuI4ZhxOUyQfxJjxj0iIsecdG3RZFbgL+aCwYYjLPTbadZoAOTIr/oGy5zWU96Kvt20RhvI8xlUuXGDmHEBHMoYFTzyyzmly5TRb6OZMHsn4PYK4p8pytSLtPFL63IgLdkflMVHkgbnR4rS5A3q5w7izcDchtidS6AORAoi4FxbHqVOqflSRQ61jQ5UHfbm7GXLwp8/c11bvoAX777AJ+tlQXig4G6jNCXyVYZ9IinYcTTMAFYw2DwVu6rGfBkrnjFsEB7nP3xV+/V9YMy0DC46KnMp2HA9TbVNZq543Ncr10mBa6mZ2apue9hVud2mdT8WF5jZrVOvHIDF+zikS2SaAXaUjgfqcIT+bPLurN4cyAHMtR5CMheWXur82S6ANCdfBGo+8XmRNhKIb8tzOmnXn9bX9wMgNEexAcz/V3M9Mq3ywg1GAzDrMhngF/UiItalbiex46PRuOm9OKHD7Oatr75DXMao528F3WbyrSqfNQY505PcxkBo9cnOgLze4zICrYwty+WtvuABfoMb2Vm8e2r8gyrJRQ5ylcE2NYAD6SNTo+VJcibVc4dx5sEuY1WQG+tzjdl5QLdpvV3zExgm8RyhzJuhrxRmBN4O+AGAfhiqRjPXiGeuDbAxTgQt2rcWiFaGWg1qXJ75+YNCqPReJ1HrLjWyjBBfFHpChpzGcosVs3TMOJ6G6enLlqYz145XVUj1CLI1Wig1DxyZZwtlZEodKvIfajT9U9UOgudzO202V6SfKltnkj7APgx8aZBbqOl3RJV52DylwCdpGfVdiAtB3a/DDZyL1vJ9wXa9HtAka8gN0xHJ4U4JktlGKEHA6UNtJ5AOzgQd22VcYb4TanpzUAGuJFb9G9zJ+hoNEayEMNcloW5/btpPdU9GIxmhBkno99cmA2h5hW+kH2aZmEOCm9itQDr9GU9Ot555naKRSZMc2yRlgCPlifMLy7njcQXAXJgJ3Uey58DdJqe5PF3StZGoXla7MQ+tL3pFN7ADGyi1JeOzuXPeL8xAXwwwDyWHMPsjQ8GWq9qfNBT96wm4KVxmy2TxQdXwI0keTUDXpfx5O57QGmZCsCgbd2zIh80zGgprIABcB7uSywVoyZ1vqwXqsiBtSMU63RHldN9InXVlBslCjgX3rF6HgDvEl8MyG20BnqwrBTQvXnR8gR5NnkrdmTR0DRGiYdGqiwqfFbfywiWpZNzgriZAW4hrvRWjdsOTu2tWGutWFU+wuAVcO70HGcP3arx0VtQW+5Fj7jqERetMM6qXJmpTfatRhNj57HmVomDwNtX5wbLLfxGw+n03EAdnr3inZRb3NVcA8xs9V1anrTs3LLeYHxxILfRukM0WFYsvxDQQUtFkDc7vPycCmehTb/7dooyrrViIe7ZLVCTN66GcQb4CD1/KmWcPwALzCmYb2Z9UNY07tsFuVXjFPy0LL+eqQ0axozT82CGEcboyQfXgBpAhnEa4DYNSTRT4dM0NSl2hdVWWeBtIT/Derm9304HmU63SSuFbtsQiSLlLZj/AHi7aAPynJXYcgdsEEllvcykmeJlRYEeKiMyP7STtlDfwTpCNsr82we8D/Dp07jWClXn852cmEepQLtKXC9/IwZlMGjjeNn24Vg2Jv9bb4YX0lTWdnk1w5Kehu30tN77oA3G0eCmJ3gbbTCauc3W7oJlMYG5fa3dYq0QdW6w3PW5AbotkKhyO23TMS0VIhnRBKyCMr4I+2RnJuaBvMWKi5VxMOR3s11oGaFyEsrbr6cqpFaKX6cPcAfkxh0vHoK4niGn7Z+ZbrLRI5QCtJ6VccAXB6ahhaP9g8Ko7NMOlaPab7OtMpL0N2YlOn65mk4o4zi3yQyTvaLVAl2jzQbmCtPDtKCJEqdEthAnQF9mK2KtUKVut0NPdU5Dun+1gHdGfacBeK/jz0bGdk2DfM+VllKtO0UPlR4tTwDtYLraEFgpqU7O7XBDswLd2gw+xLVZOj6hZ0vF/ikzQ3zc2CkAWJgDs7WiNLSxslfjRufPMJ/GkvMrk5btWyzjOEy/bfsX9Ty/gNoEYD5gvTSYO0t9iDtAB9n8PtTJNGeb7HWstIbtPcF77zYI+GJjC/IzrDAbUsB1jCKoA2KwB8stvTTLyCfq1CTz/I7OLcyJCrcKXBFwk+9UgdO/CebjYq1MdgpRyd6KndS4vRHIQBuzjCG/AcvzV6wvbiFubwyyd3zSmMaW279peKKZ22PMrPO1cWyQaaEBTEifJxF/nHRwGmXmkSxhoG/8csAB+EaJ+3BPReE+wxaVk79m/9wzzsRBIMmXSzDhWeNA1S6GOpDVzqQHnorItpN2VMXGDIsATqf5d3ESwFuIL52bM/AXNY6JfX6n4zTdXSF0LPhimczTXjFgwIiReOYW4tSG4crCXJet0/2bbwKaQW6MWgg9PaNrJqyZn1OuzNRJamG+XiwA9vVwDNDtUEUH0MbbTh68ozrDn1lwvBeBNTPPYfC+F/7ZWC/8AACXu1sAPw4Cu8gycRKECpLXURSBMlJDyHxv3AG489s46nvjlWsyOkVRiIN44tZSgaPGLUhDVgqAWVWPuJnpJqCbMsD8wuXJA6FplaPGV29dMyVPocmJZFLksyo3w3RSWh5TOwF98svnO0HJyz0M1GqvzDcI2abOxsx6bCq4QLfq24O6s52ADdhpdD8sCvfVB7grY16Otzf88CRgB4SKeocdSjpKYOOF0+khgFN4Uz98Vt+LErcQX1T4TCprqywqfFXB1tqgMPdVOUDGjiuD6zjMoBxZH/wGjes4kPHm2zTL8MalHdP3kapyZWDmF05YME/PJp+eW660mkar6FmZ6xnWFt5q/tRWibvqfFnvFuhW6JPt40N9sw1tUpv/4HhYJf3i7YHcj5NYMVy0GjqWfYB46Tn1vUwPARxwVPhiEVOIL8qcKHGrzK2lYsGtfQvDbKDtK3Nrj0xqfB6BojCBWik+/Qxvq8bpiBe/rhu24bRvufVerbfhqxnetrOTdHoqbWDGeZy5A/FVnS/jETmg221jp3ubbQlvvzrtftgzztSWHaIZyFttxFY7VbgCZtqOcHeq3WtnC4GbzktZKgCvwjd2illtlRDEbSenVeTKQsoqctK8gLUy2SHrKHGrsNc7b9z5Ns8K8a0a5ywWvTm5qPlFEgbKqOWktShyECWegrlZV7MBlhPDJKBnO4Yo743FYlU6gTvddEsk9u9TAbgkDmj/2XiXDfLeG30v9eAWyjWkQz17BbM8LLzJ92yAA6uV4kPc+01tmsVmUXCGGtLPJRnZ2Bbm9Lndo5nGjI9GY1C3WVWvMB/NsLn7cx3louYy1rHly7pidkLrky/fZ1tFEXvFmPn7fOMPXfbFO7cwN4Aizzm3VouFtLVbJoHuAh2IqHG4uy5rq7yxfbtH7HVyqx7oMEcS5Gc7W8fa0xTyseU+w4GQ2C6xoYX0uwjgdr6vwul0CnFqudDOzcUTn2C2gs7MUCTjtolP7cdo1NJeaq+stsOqxm/eirIQp/bK6J0cbEzPOFezzaKIT47ZI7dtV8uJydgVMxPUAhzjtE4WWwUz3Oe7QI3xFfm8febtUAJ0Ot9G0i+/g327VZyNbTRyB1NsQH7mhUvFKSDPhbTuwnUfGzrI/d7Ae/5OAb6k81U4hfgCbAbi1lJRFOLAFtxWfdM/C/HwMlsVrZVhbJW5cVw+B+LuA7S4jk8b8whCx16xbbfLRE9esBYLSOcnPI8c80nOkJc1z02wJ8ll5MpU0jyPAfqy3Pmcdo6NnH2w837dIu6ZZzRSYL9wid5iHGLZLIW3KSa6DAmYi6wVH+Dz/KAKj0FczRDXpB5rqZDyfCW+NEu4QRaYe7ZKCDIOxBd7JT4E0WnTnIdaQdM6UcuyOUp99s7N/OIJ+B2eAIBprPliqczFbdT5PI0CfdmUJGGQywGbpfjy/gTc+BLYxQVdbmWAy5e6IvzIXQ8twV876iQ0Xe6LG+83wipcCnFrnWCdFlLj8AAeuZgAsI4HH2dwL1YLsVVuUJt3ed4WcK/2CrVWuNErXFsU9SfmTs+NKrcLp830EC1FrJQQzAmYg+ocK6gV5vrMVqHbiIrtkM1CO1cFceix8AgYddTwQ8nGOoNXF4mjRpyk5km88SjA58+NKrfzfYjr7TT3zzifvBqHY6mEwnZu2meM2/dmLvB1YD6lcPPrtRwf4mRF+fO48EewBFX5QljSRtg8cpgDW+5SoE+/lVOFb7b7Ko5T524BzDxu1pcE35Oya//H2O5d5slPCFnLGUib37GZALidpsjqCylxBuKLL77kozD31Djg2Cq2o5NOM5jg67zWbbFUvGGGC8wB3yd3Xz5B/7Qzn8bCtrnN2kIbylHmiiyro8pBLJZ53SjYhZfBHGRd+ercaWMI6MxCbaDOZcjxzt/ScbZ3XQ3W3f6Psd077rHNQLTd5Z2bYYAv0wMqfJ0fUeK2c9Py0xt+6KjxpZ3UVgkvMw07zG+1VDT0MvyQlO8dIE7HJrVZsP7mhh5yoZRVzMTesHVTVW6nWYvF+uW29zQF8/lckFLndHE3QPeUuS/rgx1pOcr8Xo+zM0Ro3WUAPg7yx8bpH4J1HGSLBN6AA0uJCgcCVopNH7BTXCVu1k9Pjdvp1FaRhtu5uQ5P9Kf768Om4T7td256Kpb2W6Vu1Ap3S2LbSbp8zqheFjwMc7oYHMyX+RbQpKrlxE1WhLNkAa8mOkKiAXQeIYzYFZIXLsgf4G4bhetTDG5mGgdwttMzpsLtfA/WzugVD+LOH7a/lfddkfZN07a35PuxKHEQn5yoct8T92ML8u3NQFa1p5S5PQkt6Uin52KHkO+sIvaouoG5MhOYfasFcnU+VbMSmjR3C/FAIVGwr5Wk4wH7uohs5Pt/+mGP2HGdJMVfLrwBOcDtb1+Fz58biNP6PIhv1LjyP1dF7wM8tbiAq7i1MjBGudieYa4V/7AsW8b6ffu2ILMBPV/OLHydZaBAXz1xu04WieyqckURDSwwJydUqs6dlDF1ToNYJxzQbZM5Zc5OA7/PikautDquHieEKcj63HfUyhd80hBfrWeo8aR9QvNxAKfTvWmsEvfzSSCOVY1bFTtNc7/nhFXhAzmiXWWOINCXjk1sR6Vw01JBIW6/L1bL/H1R5QswPYvF2QhY1+WaDE5K23FKzhMAXwSdsQE6sFXpfmZJRyjC+3fLoYlroR3K7BE7nnDagfxeVm6nKBqCVaDGQ+p7M4+5fA+qcH9aBOIbv5wqc68cVo3zixX1ye2IFX/kClXliz++QDBwZye2qpuqcVon/eRigTT5vqj1ZT0wqnyevH5lRrIsCxmA+bIO1vrh5wnYJa69ElHpdjlI3jUBs0IYcKWOiy6gP0tImNBo+ctA/gVBuwjQoSgAN9sGb+9nAU6+Z6lwW34M4kFwex2cwFZ1e58xgC8PofKmLZaKmgeDzD+p9RK73Z6DOLVZOH885pmvqtvt1FScKoebhqpvSu8UzEGTI6HON1cEa5nrfF6lg85KqPLkfCakx9ebBb7whJiKc718uVM0hbEkpPXFIMbK1oYA96azEIc3n/PF4ebbqHFSjw91/zMWBqtPvpnn++WJoCAPAXo0SnQ8rbD2P31LxfohwIbQiPjlXlJFfiy/idUytckpxhkZCZJ+M98hP0jbyPLGVHkK7KF0gqg5hu/uJFAA97sYtbI7iKWR265E+mx4+2X6AKfzOYjT9I5d4uaLdm76dW288bStsmRnjjj2RiDAVeVYOz83QxAD4XRuemp8450z5TkdnP48kKudGeLT69/gkZdkAGucxGEObHJMo1y26jwH6ACv0snHmsZfcK8tbDQEvCRq+XGKE0EC7oeNWjktnP2oaacgrwTebLqAGg+pcGBrpSzpfYiTckUQp52dtmxS5sZWAaKWih+cxWLD+uIU5ja4NwQ5ZSLdwSm9QQiA45mv07aPtt0MACcWSxbM5zLtK+Scbc1YLU5+D+LOd0RUOpkZhXqg7mjEVvWBMM1h1a7QJ+3qNmrliwB1QTnB9ZILb++3WIXT6blKPNTuBfI+0APgjgw/XJbHg/fmRiDAVeAE5rZc9pZ7Mo1CnKpxa6v4+YMK3B9+OLd9UeF0OuCqcszfubIJvbNg7lstcKdv/fG13JCKX9I6X8BC3U+yXR63DlGkjq8zqGakudcL9NUgPzWwe7atFtxLOf0ADvAQd/xwfxr97beNU+N+zPkU1y644M5R5Vxs7JS5PAp0LriRKznKmwt3BAsFO5aNMI0P91S5U8i8XBbbjh8tg/lSDIW2nRZQ53PxG1WeVOn0h3/Sk4A90KaikGy+E8A+tJvVAj4L5KeC9l5tKainCby5ulMAJ9+jKpy2IaTEaX5lpwcsFU6Nz3kdcG+XMBqjATRWZS65PT81YmUt24W5/c6p8Ump57Wd8Nu1V2gCTpX7MMc6G3CSsDB3OkFJBNU5KQfIA/qS3vkCdmdO2jDLzMD0FhA+MezZC7KMtgRBfji0966/sD7ReopskdYAB4QQp9NCat2HeCwI0J1OzmW++zvnJiDbwennodO5Z63EPPItqBn4BKaHYtMBSu2U+bd9GfP2jLsNbiTLBtQu/900ntXCqvMKoE9tJOnpcrsLEvtZd1doa/CmNveOoM+B+wLyQ8B9p3V2gTcQBfgmX0yF0/m1EPfLDKlxbnHmNL6FErJU7PC9VFjFvKjweTodTw6Eb+bxn3ToWCzJ2te2cuF3eK5PsA3YPT4xKZU3Cn5Nw8J8KSoN86VI59Jh/e50UWQAfVmkzTIyCQOTsmyGvQCfqq9nnbSKwLrq/4ago5R9o3qz1k8LeDPTmqlwbvo8jQP9Oo+xVAKxqPHg8pbt7XTYYchSsScCiYqOPVclNAxRHL4SX6YDgNcJGsq7nJw9v9wH9bJADMzn2pZsNHLVuZ/OL7QR1EOTs3ebvQEfq7NjvXZd3f8t+o3rbQXuZFmtAU6nSyDupV3S0ekW4qH2U2hHlPmSPEdtz79HGGi4St2CW4GH+VKnV1/qNnzfG7d5RjN9WriLnADfZtkk8L0LtX71wrFYPNU9lbUWs1Xhmerca44I6KFpyIC6nxjxWcWdg0cAfod67+cW/Q51FgkuCYwq1Pcmvz8/psLJ9xyIGx/CNI3/O6a2mWD98sLwvXLLm1AnaOyuTf87bWGVGiehsEI4qMC5TCGLZfObGUOeC3Obh/zc2C2k3Lladx7XRjrN/vTzb5Y9rdZjs6t2szMBvqDOc92i37Gu4uOyBtxAxGIQlFOgwp1yciHuATw61JBR49RWUZnATwX1z+mwQwpzIO/OzqVsMo3Cv3ZIohMKULBDBJlOT/t9o1rt3Pl55/CzVMCcVBtV5yDlIADkmEr3povUdYZajyWp1hCxantBvgDuW5DvBe4zQhvI2vJ7AxwQqnCAhziXnoO4ClgqMbB3ignaBnqukz5vZbFTSJN8Ve4HB3B/uvu9MdAlQVU5icVi2YA4H+ZAhjrHNs3UHlIOl36zTMz0UDl+FIA9lKzRBWIzNV1Ul1dP/1v0O5ff5BgTbtlkXZlgjwLc+82qcPI9CXFOiQfKMxzc/egMdW7Ioa/K6bBD/8o+pco5iMfUeCu7hY2l2Lgqn+DMdH4SsEphvknvlbdxSvw0AKqAzszL8sEzbBg/3gTcvXra3qL/hqCdVWeG+mbLrAC4U54H8E1dPsSZzs1wmyJWCWerVISjCOcYDTaq3B+lQoEuCfbZKwk1Xn2lrhh7hSXLXJvTWwgepiRtEuZ0KWJWi81Lq/PhnAN0ms+fF1ip0Y5Sp5yIzBfG7nAHmgK+DuT3AG5gX3hH5uUAHGgE8ZAS9zs3lzz8dGeaxP9WyO7opM9J4abZOz0dJU5UespWsRF6hgpV5vROTk6dZ9kttsMTiB+8FsghVb4A0/PLF7AKYE7z+Ok35ZE6SXFFQOfy+dO5eXayFOpcokKQZF0hlITfrIry5SB/o9DOql8AL1G5iWmbJYipamAD8dAJg4U+AX3QUgmBWwhqhTKVTv3wqK3inQCkFojzAK2EvVJiqygLymTCmKVCVLkD5rBfHoM5rS7pm8P9HrVbvPYBEfjGlHhvqHOFCKOragf4Y0xYPg/ye4G2jYK1KW5DAbyD5QumZalwIAzxlBIPlM1aKnQes65bDDHkXibMrS5rsfgwn8rYKnq+Lrfk7Z2egXxMm6tCBYYm+mAnvvb0Gyxog0qbAazIN7d5/PxkEgtlZlq27RIq24ti1dxAsYeyHgH3SzBxozgDtG1ktaUlwLn0MYD78zmIMxbIBuKbMj2IE+UdtVS434GTUony9m/ND/1e4b2FOZAeP+4H75G7vzlbJfZbHL6atdOALRQDvxeLxYeuB2c+rwDmfv0pdZ5qOwpsF6eSwHymfLaOUDRS7LGsXeFuGo9aaQ5tYD9wA8XwjtbVGuBAHOJMWYYqZgb2UUuFluVvi9C2abgfcF74NN2FuU1rQzL80EYK4k1HqyiAfe7KRnVHVDmBHuuXR4Edm7fO2MAcJD9IGV6SDZADgE4Cnckjms/UwdaTCj9D5T7QFe6qsrPzbOAGOsA7kUYMcGZaF4iryLxAGq5twek+f3LWN7NtY2qcs1dccK8wn9pCQZ9umOuBJ9IG8nG/c2PzZqGICnczAhu17ExjLJYUzL189mewvjk224pbBmCzHEGgR/Js5sfSePUsWQ8GO1dEDfrEIO8CbaDJaWlveEfrrAW497sJxCO+eNBSybJattuw5KUR1Cf3lTZV5RzMbZ61fn6/4qDLjVDh1LjbEZpYGMba4F4FF/W//d++Kucslg3Y62DuzN+0x64M5yPbP7d12Go3IQF2BtRpfcE6U7ED2LlqQrH/88iPADcgv9wvUd+hfMw0qQrf1MfAmPXEUxB38jOAD7YtYat02l8sX1IwB1agAzKV7KvwEMSL9ljJTrqBNmOvMODmyohaLLkwh5vPmQ8vDdM2Vp0DyAG6XXx2eZl8bJpUOqbOYL2p6AB2rphQ2y4N6+SjkRF0FLyTdbcAuPc7pcKdNCUQj6j4WJ0pW2Wjgrmd27FReAWeei45hTmtlwM6FyGA+99DdfPf43X6kPafjhi1V1KqnFXi/mcGzOHlm2cmrRaQsrzJXJrgNDupVqXnpGPqDdYtiZ3Abqtq+zzyhl2zxe1qBO9kG0oB7qeTqHAvXcz3lkJc9MafRDt6xwJsuKqczvO/A2m/26+D++6r8V2ft5ICdyA2FksrmHvtCKZhfncHul94R6hH25CKxiNj/GJ0OlkklHH/KhtD//LaQf6kaQVtycovVeGtIE7L8iGeiI2lkqvGnTRl2z2lbH2bw9YS9qzz7rb000sgvn6mlyMrQutTtP7dz+QJGjYdn9+ZF6l3kyb2GwJBE8lL60yu4lwOZG6yKk5t2tCOn3mjVhoqbqByReTkrVXfsTJKVLj3e1N3jZ1C80cO1mC7QtOkUZFX+qq3kDK3v0v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-    "plt.imshow(e1_map)\n",
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-    "from the convergence map we can compute the convergence profile, and from the e1 and e2 maps we can compute the tangential shear profile."
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-    "The getTangential function uses the e1 and e2 maps as an input, along with a map center, and returns e_tangential and e_cross maps about a given center. \n",
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-    "The function also returns a radius map and an angle map, which is used when computing radial profile with getRadial"
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-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:248: RuntimeWarning: invalid value encountered in divide\n",
-      "  angle = -np.sign(from_cent_2)*np.arccos(from_cent_1/np.sqrt(from_cent_1**2+from_cent_2**2))\n"
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-    "plt.imshow(et_map)\n",
-    "plt.colorbar()\n",
-    "plt.show()\n",
-    "\n",
-    "plt.imshow(ex_map)\n",
-    "plt.colorbar()\n",
-    "plt.show()"
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-    "With the radius_map and angle_map, we can calculate the radial convergence profile from the kappa map and the radial tangential shear profile from the e_tangential map, using the getRadial function"
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-  {
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-   "execution_count": 12,
-   "id": "e3d066a0",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n"
-     ]
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-   "source": [
-    "kappa_radial, gammat_radial = mod.getRadial(radius_map,angle_map,\n",
-    "                                            r_bins.value,phi_bins,\n",
-    "                                            kappa_map,et_map)"
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-  {
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-   "id": "f89da817",
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-   "source": [
-    "plot the radial convergence and tangential shear profiles. Note that these profiles are not averaged over all angles yet, meaning that these profiles are 2D (radial and angular). This is useful for miscentering which leaves anisotropic signatures on the resulting lensing profiles"
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-   "cell_type": "code",
-   "execution_count": 13,
-   "id": "080ff2f4",
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-    "plt.imshow(kappa_radial)\n",
-    "plt.show()\n",
-    "\n",
-    "plt.imshow(gammat_radial)\n",
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-    "We can recover the 1D radial convergence and tangential shear profiles as follows"
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-   "execution_count": 14,
-   "id": "5c6174be",
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-    "kappa_1D_radial  = kappa_radial.mean(axis=-1)\n",
-    "gammat_1D_radial = gammat_radial.mean(axis=-1)"
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-    "Plot the 1D radial profiles"
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-    "r_bins_mid = 0.5 * (r_bins[1:] + r_bins[:-1])\n",
-    "plt.plot(r_bins_mid,kappa_1D_radial,label='$\\\\kappa(r)$')\n",
-    "plt.plot(r_bins_mid,gammat_1D_radial,label='$\\gamma_t(r)$')\n",
-    "plt.legend()\n",
-    "plt.xlabel('r [Mpc]')\n",
-    "plt.ylabel('Lensing amplitude')\n",
-    "plt.show()"
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-   "source": [
-    "## Miscentering\n",
-    "\n",
-    "We now repeat the above procedure, but this time we use an incorrect center (relative to the true hale center) when performing the calculations, the exemplify the impact of miscentering"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "id": "13660944",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n"
-     ]
-    }
-   ],
-   "source": [
-    "# First we define a miscentring parameter\n",
-    "R_mis = 1 # Mpc\n",
-    "\n",
-    "# find new center based on R_mis\n",
-    "_phi_Rmis = 2*np.pi*np.random.random()  # isotropic angle for mis-centering\n",
-    "\n",
-    "# mis-centered coordinates\n",
-    "center_1 = R_mis*np.cos(_phi_Rmis)\n",
-    "center_2 = R_mis*np.sin(_phi_Rmis)\n",
-    "\n",
-    "# get tangential and radial profiles\n",
-    "et_map, ex_map, radius_map, angle_map = mod.getTangential(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
-    "kappa_radial, gammat_radial = mod.getRadial(radius_map,angle_map,\n",
-    "                                            r_bins.value,phi_bins,\n",
-    "                                            kappa_map,et_map)"
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-   "execution_count": 29,
-   "id": "1cb19534",
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-   "outputs": [],
-   "source": [
-    "def plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map,ex_map,\n",
-    "                       kappa_radial,gammat_radial,r_bins):\n",
-    "    '''quickly plot the convergence, e1,e2, ex,et and radial profiles\n",
-    "    '''\n",
-    "    fig, ax = plt.subplots(2,3,figsize=[9,6])\n",
-    "    ax.ravel()\n",
-    "\n",
-    "    ax[0,0].imshow(kappa_map,origin = 'lower')\n",
-    "    ax[0,0].set_title(r'$\\kappa$')\n",
-    "\n",
-    "\n",
-    "    ax[0,1].imshow(e1_map,origin = 'lower')\n",
-    "    ax[0,1].set_title(r'$e_1$')\n",
-    "\n",
-    "\n",
-    "    ax[0,2].imshow(e2_map,origin = 'lower')\n",
-    "    ax[0,2].set_title(r'$e_2$')\n",
-    "\n",
-    "\n",
-    "    ax[1,0].imshow(et_map,origin = 'lower')\n",
-    "    ax[1,0].set_title(r'$e_t$')\n",
-    "\n",
-    "\n",
-    "    ax[1,1].imshow(ex_map,origin = 'lower')\n",
-    "    ax[1,1].set_title(r'$e_x$')\n",
-    "\n",
-    "\n",
-    "\n",
-    "    r_bins_mid = 0.5 * (r_bins[1:] + r_bins[:-1])\n",
-    "\n",
-    "    ax[1,2].plot(r_bins_mid, kappa_radial.mean(axis=-1), label=r'$\\kappa(r)$')\n",
-    "    ax[1,2].plot(r_bins_mid, gammat_radial.mean(axis=-1), label=r'$\\gamma_t(r)$')\n",
-    "\n",
-    "    plt.legend()\n",
-    "    plt.show()\n",
-    "\n",
-    "    fig,ax = plt.subplots(1,2)\n",
-    "\n",
-    "    ax[0].imshow(kappa_radial,origin='lower')\n",
-    "    ax[1].imshow(gammat_radial,origin='lower')\n",
-    "\n",
-    "    ax[0].set_ylabel('r')\n",
-    "    ax[0].set_xlabel('$\\phi$')\n",
-    "\n",
-    "    ax[1].set_ylabel('r')\n",
-    "    ax[1].set_xlabel('$\\phi$')\n",
-    "\n",
-    "    ax[0].set_title(r'$\\kappa$')\n",
-    "    ax[1].set_title(r'$\\gamma_t$')\n",
-    "\n",
-    "    plt.show()"
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-  {
-   "cell_type": "markdown",
-   "id": "e9720a7d",
-   "metadata": {},
-   "source": [
-    "we can plot all of the results at once using the plot_maps_and_profiles function"
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-   "cell_type": "code",
-   "execution_count": 30,
-   "id": "32772d61",
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-   "source": [
-    "plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map,ex_map,\n",
-    "                       kappa_radial,gammat_radial,r_bins)"
-   ]
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-    "We can also investigate how the 1D radial lensing profiles change as a function of miscentering"
-   ]
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-   "source": [
-    "Now define a miscentering distribution"
-   ]
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-   "execution_count": 31,
-   "id": "38b199f1",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# define miscentring distribution\n",
-    "R_mis_max = 1 \n",
-    "N_R_mis   = 15\n",
-    "R_mis_arr = np.insert(np.logspace(-2, np.log10(R_mis_max), N_R_mis-1), 0, 0)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "id": "c17883c2",
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:248: RuntimeWarning: invalid value encountered in divide\n",
-      "  angle = -np.sign(from_cent_2)*np.arccos(from_cent_1/np.sqrt(from_cent_1**2+from_cent_2**2))\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:299: RuntimeWarning: invalid value encountered in divide\n",
-      "  kappa_radial = _K/_N\n",
-      "/Users/alessandrafumagalli/DESC/CLMM/clmm/modelling_ccl.py:300: RuntimeWarning: invalid value encountered in divide\n",
-      "  gammat_radial = _GT/_N\n"
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-    }
-   ],
-   "source": [
-    "et_map = np.zeros((N_R_mis,kappa_map.shape[0],kappa_map.shape[1]))\n",
-    "ex_map = np.zeros(et_map.shape)\n",
-    "radius_map = np.zeros(et_map.shape)\n",
-    "angle_map  = np.zeros(et_map.shape)\n",
-    "\n",
-    "kappa_radial  = np.zeros((N_R_mis,N_r_bins,N_phi_bins))\n",
-    "gammat_radial = np.zeros(kappa_radial.shape)\n",
-    "\n",
-    "for j in range(len(R_mis_arr)):\n",
-    "\n",
-    "    _phi_Rmis = 2*np.pi*np.random.random()  # isotropic angle for mis-centering\n",
-    "\n",
-    "    # mis-centered coordinates\n",
-    "    center_1 = R_mis_arr[j]*np.cos(_phi_Rmis)\n",
-    "    center_2 = R_mis_arr[j]*np.sin(_phi_Rmis)\n",
-    "\n",
-    "    et_map[j], ex_map[j], radius_map[j], angle_map[j] = mod.getTangential(e1_map, e2_map, [center_1, center_2], dx=dx.value)\n",
-    "\n",
-    "    kappa_radial[j], gammat_radial[j] = mod.getRadial(radius_map[j],angle_map[j],\n",
-    "                                                      r_bins.value,phi_bins,\n",
-    "                                                      kappa_map,et_map[j])"
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-    "R_mis_ind = 10\n",
-    "plot_maps_and_profiles(kappa_map,e1_map,e2_map,et_map[R_mis_ind],ex_map[R_mis_ind],\n",
-    "                       kappa_radial[R_mis_ind],gammat_radial[R_mis_ind],r_bins)"
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-   "id": "2dbde4d3",
-   "metadata": {},
-   "source": [
-    "Finally we can plot the lensing profiles for the whole miscentering distrubtion"
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-   "cell_type": "code",
-   "execution_count": 34,
-   "id": "7e458c10",
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From 9725e5497574e2dfb3a7b844403a74a941c9a1b0 Mon Sep 17 00:00:00 2001
From: AlessandraFumagalli <alessandrafumagalli95@gmail.com>
Date: Fri, 4 Jul 2025 14:06:05 +0200
Subject: [PATCH 14/14] fix import bugs

---
 clmm/model_profile.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/clmm/model_profile.py b/clmm/model_profile.py
index 0e4cfb10e..7ce24a1dc 100644
--- a/clmm/model_profile.py
+++ b/clmm/model_profile.py
@@ -1,8 +1,9 @@
 import numpy as np
-from clmm.utils.constants import Constants as const
 from astropy import units as un
-from clmm.dataops import _compute_tangential_shear, _compute_cross_shear
 import clmm
+from clmm.utils.constants import Constants as const
+from clmm.dataops import _compute_tangential_shear, _compute_cross_shear
+
 
 class profiles:
     '''